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github | jacksky64/imageProcessing-master | matrix2angleaxis.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Rotations/matrix2angleaxis.m | 2,499 | utf_8 | c9fc88c002549f547352b67cc8689c21 | % MATRIX2ANGLEAXIS - Homogeneous matrix to angle-axis description
%
% Usage: t = matrix2angleaxis(T)
%
% Argument: T - 4x4 Homogeneous transformation matrix, or 3x3 rotation matrix.
% Returns: t - 3x1 column vector giving rotation axis with magnitude equal
% to the rotation angle in radians.
%
% No... |
github | jacksky64/imageProcessing-master | quaternionproduct.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Rotations/quaternionproduct.m | 818 | utf_8 | bcfe792d9518a1c110b9957970f4f7c8 | % QUATERNIONPRODUCT - Computes product of two quaternions
%
% Usage: Q = quaternionproduct(A, B)
%
% Arguments: A, B - Quaternions assumed to be 4-vectors in the
% form A = [Aw Ai Aj Ak]
% Returns: Q - Quaternion product
%
% See also: NEWQUATERNION, QUATERNIONROTATE, QUATERNIONCONJUGATE
% Copyr... |
github | jacksky64/imageProcessing-master | quaternion2matrix.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Rotations/quaternion2matrix.m | 1,413 | utf_8 | 7296cadf62f6ca9273e726ffd7e19d95 | % QUATERNION2MATRIX - Quaternion to a 4x4 homogeneous transformation matrix
%
% Usage: T = quaternion2matrix(Q)
%
% Argument: Q - a quaternion in the form [w xi yj zk]
% Returns: T - 4x4 Homogeneous rotation matrix
%
% See also MATRIX2QUATERNION, NEWQUATERNION, QUATERNIONROTATE
% Copyright (c) 2008 Peter Kovesi
... |
github | jacksky64/imageProcessing-master | newquaternion.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Rotations/newquaternion.m | 652 | utf_8 | 57135243008eb6d8ae64557d2f013e6f | % NEWQUATERNION - Construct quaternion
%
% Q = newquaternion(theta, axis)
%
% Arguments: theta - angle of rotation
% axis - 3-vector defining axis of rotation
% Returns: Q - a quaternion in the form [w xi yj zk]
%
% See Also: QUATERNION2MATRIX, MATRIX2QUATERNION, QUATERNIONROTATE
% Copyright (c) ... |
github | jacksky64/imageProcessing-master | quaternionrotate.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Rotations/quaternionrotate.m | 2,026 | utf_8 | e0b6a4a18c8be41ee01226e17cbd83e8 | % QUATERNIONROTATE - Rotates a 3D vector by a quaternion
%
% Usage: vnew = quaternionrotate(Q, v)
%
% Arguments: Q - a quaternion in the form [w xi yj zk]
% v - a vector to rotate, either an inhomogeneous 3-vector or a
% homogeneous 4-vector
% Returns: vnew - rotated vector
%
% See also MATRI... |
github | jacksky64/imageProcessing-master | inveuler.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Rotations/inveuler.m | 1,296 | utf_8 | 68fbee86dde87b43540b185a69fd8bfe | % INVEULER - inverse of Euler transform
%
% Usage: [euler1, euler2] = inveuler(T)
%
% Argument: T - 4x4 Homogeneous transformation matrix or 3x3 rotation matrix
% Returns: euler1 = [phi1, theta1, psi1] - the 1st solution and,
% euler2 = [phi2, theta2, psi2] - the 2nd solution
%
% rotz(phi1) * roty(thet... |
github | jacksky64/imageProcessing-master | ternarymix.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Blender/ternarymix.m | 13,368 | utf_8 | 53527c33bc58e77326e03f0354a5bbb6 | % TERNARYMIX Image blending and swiping over three images
%
% Function uses Barycentric coordinates over a triangle to interpolate/blend
% three images. You can also switch to a swiping mode of display between the
% three images.
%
% Usage: ternarymix(im, nodeLabel, normBlend, figNo)
%
% Arguments: im - 3-element c... |
github | jacksky64/imageProcessing-master | binarymix.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Blender/binarymix.m | 11,564 | utf_8 | 53c5c89d010c8dc56ca1daef824526f9 | % BINARYMIX Image blending and swiping between two images
%
% Function blends two images. Each image is coloured with two lightness
% matched colours that sum to white. Like a ternary image but binary!
% You can also switch between blending and swiping.
%
% Usage: binarymix(im, nodeLabel, normBlend, figNo)
%
% Argume... |
github | jacksky64/imageProcessing-master | logisticweighting.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Blender/logisticweighting.m | 3,064 | utf_8 | 2896739e6134ef8ef15bfd4bc3726f12 | % LOGISTICWEIGHTING Weighting function based on the logistics function
%
% Adaptation of the generalised logistics function for defining the variation of
% a weighting function for blending images
%
% Usage: w = logisticweighting(x, b, R)
%
% Arguments: x - Value, or array of values at which to evaluate the weightin... |
github | jacksky64/imageProcessing-master | cyclemix.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Blender/cyclemix.m | 9,035 | utf_8 | 3290a5ce842ce329f1eb6607a37fd6af | % CYCLEMIX Multi-image blending over a cyclic sequence of images
%
% Usage: cyclemix(im, figNo, nodeLabel)
%
% Arguments:
% im - A cell array of images to be blended. If omitted, or
% empty, the user is prompted to select images via a file
% dialog.
% figNo ... |
github | jacksky64/imageProcessing-master | swipe.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Blender/swipe.m | 4,265 | utf_8 | 127b092d90f1b8edeb9f165489e6bcb0 | % SWIPE Interactive image swiping between 2, 3 or 4 images.
%
% Usage swipe(im, figNo)
%
% Arguments: im - 2D Cell array of images to be blended. Two, three or four
% images can be blended.
% figNo - Optional figure window number to use.
%
% Click in the image to toggle in/out of swiping m... |
github | jacksky64/imageProcessing-master | cliquemix.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Blender/cliquemix.m | 15,564 | utf_8 | 8d782463d2676131bc2e13681c3bd26e | % CLIQUEMIX Multi-image blending and swiping over a clique
%
% Function allows blending and swiping between any pair within a collection of images
%
% Usage: cliquemix(im, B, figNo, nodeLabel)
%
% Arguments:
% im - A cell array of images to be blended. If omitted, or
% empty, the user i... |
github | jacksky64/imageProcessing-master | collectncheckimages.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Blender/collectncheckimages.m | 5,392 | utf_8 | 7f3d2bd790c314d39156748f34dce0ed | % COLLECTNCHECKIMAGES Collects and checks images prior to blending
%
% Usage: [im, nImages, fname, pathname] = collectncheckimages(im)
%
% Used by image blending functions
%
% Argument: im - Cell arry of images. If omitted a dialog box is
% presented so that images can be selected interactively.
%... |
github | jacksky64/imageProcessing-master | linimix.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Blender/linimix.m | 6,641 | utf_8 | e8891cc28a8631536ebbdaae2a9dd1a2 | % LINIMIX An Interactive Image for viewing multiple images
%
% Usage: linimix(im, B, figNo, XY)
%
% Arguments: im - 1D Cell array of images to be blended. If this is not
% supplied, or is empty, the user is prompted with a file
% dialog to select a series of images.
% ... |
github | jacksky64/imageProcessing-master | bilinimix.m | .m | imageProcessing-master/Matlab Code for Computer Vision/Blender/bilinimix.m | 5,635 | utf_8 | f1768150812e05ba0dbf1f8ac2b8e2ec | % BILINIMIX An Interactive Image for viewing multiple images
%
% Usage: bilinimix(im, figNo)
%
% Arguments: im - 2D Cell array of greyscale images to be blended.
% figNo - Optional figure window number to use.
%
% This function provides an 'Interactive Image'. It is intended to allow
% efficient visual e... |
github | jacksky64/imageProcessing-master | findendsjunctions.m | .m | imageProcessing-master/Matlab Code for Computer Vision/LineSegments/findendsjunctions.m | 3,885 | utf_8 | 1c766254222e0b8fd5326786249247bf | % FINDENDSJUNCTIONS - find junctions and endings in a line/edge image
%
% Usage: [rj, cj, re, ce] = findendsjunctions(edgeim, disp)
%
% Arguments: edgeim - A binary image marking lines/edges in an image. It is
% assumed that this is a thinned or skeleton image
% disp - An optional... |
github | jacksky64/imageProcessing-master | selectseg.m | .m | imageProcessing-master/Matlab Code for Computer Vision/LineSegments/selectseg.m | 3,097 | utf_8 | bdbe2a909309c465b0131e308d8ddc32 | % SELECTSEG - Interactive selection of linesegments with mouse.
%
% Usage: segs = selectseg(seglist);
%
% seglist - an Nx4 array storing line segments in the form
% [x1 y1 x2 y2
% x1 y1 x2 y2
% . . ] etc
%
%
% See al... |
github | jacksky64/imageProcessing-master | maxlinedev.m | .m | imageProcessing-master/Matlab Code for Computer Vision/LineSegments/maxlinedev.m | 2,478 | utf_8 | 64cc6d88009aa2a148c843e2d4041218 | % MAXLINEDEV - Find max deviation from a line in an edge contour.
%
% Function finds the point of maximum deviation from a line joining the
% endpoints of an edge contour.
%
% Usage: [maxdev, index, D, totaldev] = maxlinedev(x,y)
%
% Arguments:
% x, y - arrays of x,y (col,row) indicies of connected pixels... |
github | jacksky64/imageProcessing-master | findisolatedpixels.m | .m | imageProcessing-master/Matlab Code for Computer Vision/LineSegments/findisolatedpixels.m | 1,342 | utf_8 | e3a3768f5d589a865aa10a992e5197e2 | % FINDENDSJUNCTIONS - find isolated pixels in a binary image
%
% Usage: [r, c] = findisolatedpixels(b)
%
% Argument: b - A binary image
%
% Returns: r, c - Row and column coordinates of isolated pixels in the
% image.
%
% See also: FINDENDSJUNCTIONS
%
% Copyright (c) 2013 Peter Kovesi
% C... |
github | jacksky64/imageProcessing-master | drawedgelist.m | .m | imageProcessing-master/Matlab Code for Computer Vision/LineSegments/drawedgelist.m | 5,139 | utf_8 | 37224c54b8034d4fadf13c9b60861db5 | % DRAWEDGELIST - plots pixels in edgelists
%
% Usage: h = drawedgelist(edgelist, rowscols, lw, col, figno, mid)
%
% Arguments:
% edgelist - Cell array of edgelists in the form
% { [r1 c1 [r1 c1 etc }
% ...
% rN cN] ....]
% rowscols - ... |
github | jacksky64/imageProcessing-master | lineseg.m | .m | imageProcessing-master/Matlab Code for Computer Vision/LineSegments/lineseg.m | 3,017 | utf_8 | ff2e4a5d3f9faabdf548561ed00b22b6 | % LINESEG - Form straight line segements from an edge list.
%
% Usage: seglist = lineseg(edgelist, tol)
%
% Arguments: edgelist - Cell array of edgelists where each edgelist is an
% Nx2 array of (row col) coords.
% tol - Maximum deviation from straight line before a
% ... |
github | jacksky64/imageProcessing-master | filledgegaps.m | .m | imageProcessing-master/Matlab Code for Computer Vision/LineSegments/filledgegaps.m | 3,911 | utf_8 | f36cafd2cfd5507602b58f0ebfc6f549 | % FILLEDGEGAPS Fills small gaps in a binary edge map image
%
% Usage: bw2 = filledgegaps(bw, gapsize)
%
% Arguments: bw - Binary edge image
% gapsize - The edge gap size that you wish to be able to fill.
% Use the smallest value you can. (Odd values work best).
%
% Returns: bw2 - Th... |
github | jacksky64/imageProcessing-master | cleanedgelist.m | .m | imageProcessing-master/Matlab Code for Computer Vision/LineSegments/cleanedgelist.m | 13,314 | utf_8 | a79468f2b92f2ce262730a04d766d643 | % CLEANEDGELIST - remove short edges from a set of edgelists
%
% Function to clean up a set of edge lists generated by EDGELINK so that
% isolated edges and spurs that are shorter that a minimum length are removed.
% This code can also be use with a set of line segments generated by LINESEG.
%
% Usage: nedgelist = clea... |
github | jacksky64/imageProcessing-master | edgelink.m | .m | imageProcessing-master/Matlab Code for Computer Vision/LineSegments/edgelink.m | 21,107 | utf_8 | 25bee720223bdbc51946de674aa2d085 | % EDGELINK - Link edge points in an image into lists
%
% Usage: [edgelist edgeim, etypr] = edgelink(im, minlength, location)
%
% **Warning** 'minlength' is ignored at the moment because 'cleanedgelist'
% has some bugs and can be memory hungry
%
% Arguments: im - Binary edge image, it is assu... |
github | jacksky64/imageProcessing-master | edgelist2image.m | .m | imageProcessing-master/Matlab Code for Computer Vision/LineSegments/edgelist2image.m | 2,027 | utf_8 | 5c5436b3f23a712f883ddb43a21e1d1c | % EDGELIST2IMAGE - transfers edgelist data back into a 2D image array
%
% Usage: im = edgelist2image(edgelist, rowscols)
%
% edgelist - Cell array of edgelists in the form
% { [r1 c1 [r1 c1 etc }
% ...
% rN cN] ....]
% rowscols - Opt... |
github | jacksky64/imageProcessing-master | bandpassfilter.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/bandpassfilter.m | 1,514 | utf_8 | d98c0b715b1b05c4e8c5e415a260dd2c | % BANDPASSFILTER - Constructs a band-pass butterworth filter
%
% usage: f = bandpassfilter(sze, cutin, cutoff, n)
%
% where: sze is a two element vector specifying the size of filter
% to construct [rows cols].
% cutin and cutoff are the frequencies defining the band pass 0 - 0.5
% n ... |
github | jacksky64/imageProcessing-master | upwardcontinue.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/upwardcontinue.m | 4,042 | utf_8 | c50e198c0e568fd171e5713d3d05342b | % UPWARDCONTINUE Upward continuation for magnetic or gravity potential field data
%
% Usage: [up, pim, psf] = upwardcontinue(im, h, dx, dy)
%
% Arguments: im - Input potential field image
% h - Height to upward continue to (+ve)
% dx, dy - Grid spacing in x and y. The upward continuation height
... |
github | jacksky64/imageProcessing-master | highboostfilter.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/highboostfilter.m | 1,962 | utf_8 | ada657e25d617c134fb03bf410b0be5b | % HIGHBOOSTFILTER - Constructs a high-boost Butterworth filter.
%
% usage: f = highboostfilter(sze, cutoff, n, boost)
%
% where: sze is a two element vector specifying the size of filter
% to construct [rows cols].
% cutoff is the cutoff frequency of the filter 0 - 0.5.
% n is the ... |
github | jacksky64/imageProcessing-master | invfft2.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/invfft2.m | 250 | utf_8 | 41b97c8ab7dc15522b2c5a414bf55b38 | % INVFFT2 - takes inverse fft and returns real part
%
% Function to `wrap up' taking the inverse Fourier transform
% and extracting the real part into the one operation
% Peter Kovesi October 1999
function ift = invfft2(ft)
ift = real(ifft2(ft));
|
github | jacksky64/imageProcessing-master | lowpassfilter.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/lowpassfilter.m | 2,448 | utf_8 | 1bdb6b9b70b06af9d2bc12b6b877da54 | % LOWPASSFILTER - Constructs a low-pass butterworth filter.
%
% usage: f = lowpassfilter(sze, cutoff, n)
%
% where: sze is a two element vector specifying the size of filter
% to construct [rows cols].
% cutoff is the cutoff frequency of the filter 0 - 0.5
% n is the order of the f... |
github | jacksky64/imageProcessing-master | imspect.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/imspect.m | 4,926 | utf_8 | 1567515542e483c4deb2ccc804ff7ac9 | % IMSPECT - Plots image amplitude spectrum averaged over all orientations.
%
% Usage: [amp, f, slope] = imspect(im, nbins, lowcut)
% \ /
% optional
% Arguments:
% im - Image to be analysed.
% nbins - ... |
github | jacksky64/imageProcessing-master | psf.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/psf.m | 2,323 | utf_8 | de5c27f8dd4eb69a3ae36c1be3f20990 | % PSF - Generates point spread functions for use with deconvolution fns.
%
% This function can generate a variety function shapes based around the
% Butterworth filter. In plan view the filter can be elliptical and at
% any orientation. The `squareness/roundness' of the shape can also be
% manipulated.
%
% Usag... |
github | jacksky64/imageProcessing-master | filtergrid.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/filtergrid.m | 2,441 | utf_8 | a196e165846902098ffcbc16ddf71f6c | % FILTERGRID Generates grid for constructing frequency domain filters
%
% Usage: [radius, u1, u2] = filtergrid(rows, cols)
% [radius, u1, u2] = filtergrid([rows, cols])
%
% Arguments: rows, cols - Size of image/filter
%
% Returns: radius - Grid of size [rows cols] containing normalised
% ... |
github | jacksky64/imageProcessing-master | highpassfilter.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/highpassfilter.m | 1,443 | utf_8 | 78f60a0dd6f0ef66653d547868fad1f9 | % HIGHPASSFILTER - Constructs a high-pass butterworth filter.
%
% usage: f = highpassfilter(sze, cutoff, n)
%
% where: sze is a two element vector specifying the size of filter
% to construct [rows cols].
% cutoff is the cutoff frequency of the filter 0 - 0.5
% n is the order of t... |
github | jacksky64/imageProcessing-master | circsine.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/circsine.m | 4,364 | utf_8 | 4b2d3f6974bd3cd11dde7d3b2a600790 | % CIRCSINE Generates circular sine wave grating
% Can also be use to construct phase congruent patterns
%
% Usage: im = circsine(sze, wavelength, nScales, ampExponent, offset, p, trim)
%
% Arguments:
% sze - The size of the square image to be produced.
% wavelength - The wavelength in pixe... |
github | jacksky64/imageProcessing-master | starsine.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/starsine.m | 2,906 | utf_8 | 929263192b6c499585f5af175f649a83 | % STARSINE Generates phase congruent star shaped sine wave grating
%
% Usage: im = starsine(sze, nCycles, nScales, ampExponent, offset)
%
% Arguments:
% sze - The size of the square image to be produced.
% nCycles - The number of sine wave cycles around centre point.
% ... |
github | jacksky64/imageProcessing-master | freqcomp.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/freqcomp.m | 5,474 | utf_8 | 58a18bdbdc50fca6a82844487445c5ad | % FREQCOMP - Demonstrates image reconstruction from Fourier components
%
% Usage: recon = freqcomp(im, Npts, delay)
%
% Arguments: im - Image to be reconstructed.
% Npts - Number of frequency components to consider
% (defaults to 50).
% delay - Optional ... |
github | jacksky64/imageProcessing-master | psf2.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/psf2.m | 3,000 | utf_8 | 20d5aff861110c5341b9d6fec90f8007 | % PSF2 - Generates point spread functions for use with deconvolution fns.
%
% This function can generate a variety function shapes based around the
% Butterworth filter. In plan view the filter can be elliptical and at
% any orientation. The 'squareness/roundness' of the shape can also be
% manipulated.
%
% Usa... |
github | jacksky64/imageProcessing-master | perfft2.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/perfft2.m | 3,150 | utf_8 | 8216912bde513f4fbc7b59635da9d870 | % PERFFT2 2D Fourier transform of Moisan's periodic image component
%
% Usage: [P, S, p, s] = perfft2(im)
%
% Argument: im - Image to be transformed
% Returns: P - 2D fft of periodic image component
% S - 2D fft of smooth component
% p - Periodic component (spatial domain)
% s -... |
github | jacksky64/imageProcessing-master | invfft2shft.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/invfft2shft.m | 308 | utf_8 | 1ee9d3b8e1e84f25b0fb5503595f7bfa | % INVFFT2SHFT - takes inverse fft, quadrant shifts and returns real part.
%
% Function to `wrap up' taking the inverse Fourier transform
% quadrant shifting and extraction of the real part into the one operation
% Peter Kovesi October 1999
function ift = invfft2shft(ft)
ift = fftshift(real(ifft2(ft)));
|
github | jacksky64/imageProcessing-master | quantizephase.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/quantizephase.m | 1,944 | utf_8 | c4d5690a2daf54b63e4c2fd0ccecb488 | % QUANTIZEPHASE Quantize phase values in an image
%
% Usage: qim = quantizephase(im, N)
%
% Arguments: im - Image to be processed
% N - Desired number of quantized phase values
%
% Returns: qim - Phase quantized image
%
% Phase values in an image are important. However, despite this, they can be
% qua... |
github | jacksky64/imageProcessing-master | homomorphic.m | .m | imageProcessing-master/Matlab Code for Computer Vision/FrequencyFilt/homomorphic.m | 5,424 | utf_8 | 51155a84aab5eba10f502eb788a81b16 | % HOMOMORPHIC - Performs homomorphic filtering on an image.
%
% Function performs homomorphic filtering on an image. This form of
% filtering sharpens features and flattens lighting variantions in an image.
% It usually is very effective on images which have large variations in
% lighting, for example when a subject ap... |
github | jacksky64/imageProcessing-master | animateHessianGaussian.m | .m | imageProcessing-master/gaussdiff/animateHessianGaussian.m | 3,651 | utf_8 | 232429d2012a4e02b1901c352a995c5f | function animateHessianGaussian(fname)
%animate HessianGaussian - creates a figure with a rotationg second order
%derivative. It is calculated each frame by combining the three kernels of
%the Hessian matrix: Lxx, Lyy and Lxy. Using these three kernels, the
%second order derivative can be calculated in any directio... |
github | jacksky64/imageProcessing-master | sphere_sampling.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_alpert/sphere_sampling.m | 4,426 | utf_8 | 73ce1de08ecf14075f7fc2425b75c030 | function [Points,L,diam,topcol,botcol] = sphere_sampling(N,lrounded,angles,mrounded,ipl)
% sphere_sampling - sample points on a sphere.
%
% [Points,L,diam] = sphere_sampling(N,lrounded,angles,mrounded,ipl)
% $Revision: 1.1 $ Paul Leopardi 2003-10-13
% Make angles=1 the default
% $Revision: 1.1 $ Paul L... |
github | jacksky64/imageProcessing-master | perform_farthest_point_sampling.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_fast_marching/perform_farthest_point_sampling.m | 3,382 | utf_8 | 31f78420f1ab221fe7646f584f5d980e | function [points,D] = perform_farthest_point_sampling( W, points, npoints, options )
% perform_farthest_point_sampling - samples points using farthest seeding strategy
%
% points = perform_farthest_point_sampling( W, points, npoints );
%
% points can be [] or can be a (2,npts) matrix of already computed
% ... |
github | jacksky64/imageProcessing-master | perform_farthest_point_sampling_mesh.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_fast_marching/perform_farthest_point_sampling_mesh.m | 1,797 | utf_8 | 3e863c0d0d0a4b012240b09688d4c8ef | function [points,D] = perform_farthest_point_sampling_mesh( vertex,faces, points, nbr_iter, options )
% perform_farthest_point_sampling - samples points using farthest seeding strategy
%
% [points,D] = perform_farthest_point_sampling_mesh( vertex,faces, points, nbr_iter, options );
%
% points can be [] or can be a (... |
github | jacksky64/imageProcessing-master | divgrad.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_fast_marching/divgrad.m | 1,749 | utf_8 | 531f368d44593d78a30eea65ad3a8134 | function G = divgrad(M,options)
% divgrad - compute either gradient or divergence.
%
% G = divgrad(M);
%
% if M is a 2D array, compute gradient,
% if M is a 3D array, compute divergence.
% Use centered finite differences.
%
% Copyright (c) 2007 Gabriel Peyre
options.null = 0;
if size(M,3)==2
G = mydiv(... |
github | jacksky64/imageProcessing-master | compute_voronoi_triangulation.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_fast_marching/compute_voronoi_triangulation.m | 2,806 | utf_8 | 6ed546707daebe1eb6f945f8834ceb61 | function faces = compute_voronoi_triangulation(Q, vertex)
% compute_voronoi_triangulation - compute a triangulation
%
% face = compute_voronoi_triangulation(Q);
%
% Q is a Voronoi partition function, computed using
% perform_fast_marching.
% face(:,i) is the ith face.
%
% Works in 2D and in 3D.
%
% Cop... |
github | jacksky64/imageProcessing-master | vol3d.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_fast_marching/vol3d.m | 5,899 | utf_8 | 9ce5b72520d76d1225023aa3732b653d | function [model] = vol3d(varargin)
%H = VOL3D Volume render 3-D data.
% VOL3D uses the orthogonal plane 2-D texture mapping technique for
% volume rending 3-D data in OpenGL. Use the 'texture' option to fine
% tune the texture mapping technique. This function is best used with
% fast OpenGL hardware.
%
% H = ... |
github | jacksky64/imageProcessing-master | compute_geodesic_mesh.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_fast_marching/compute_geodesic_mesh.m | 4,234 | utf_8 | f3e2ddf4b7d47f9f8d9226288e74c5d7 | function [path,vlist,plist] = compute_geodesic_mesh(D, vertex, face, x, options)
% compute_geodesic_mesh - extract a discrete geodesic on a mesh
%
% [path,vlist,plist] = compute_geodesic_mesh(D, vertex, face, x, options);
%
% D is the set of geodesic distances.
%
% path is a 3D curve that is the shortest path st... |
github | jacksky64/imageProcessing-master | load_image.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_fast_marching/toolbox/load_image.m | 19,503 | utf_8 | 16a3a912ce98f3734882ac9fe80494c2 | function M = load_image(type, n, options)
% load_image - load benchmark images.
%
% M = load_image(name, n, options);
%
% name can be:
% Synthetic images:
% 'chessboard1', 'chessboard', 'square', 'squareregular', 'disk', 'diskregular', 'quaterdisk', '3contours', 'line',
% 'line_vertical', 'l... |
github | jacksky64/imageProcessing-master | check_face_vertex.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_fast_marching/toolbox/check_face_vertex.m | 630 | utf_8 | 5112ad0482fa3700123a6c770f8eb622 | function [vertex,face] = check_face_vertex(vertex,face, options)
% check_face_vertex - check that vertices and faces have the correct size
%
% [vertex,face] = check_face_vertex(vertex,face);
%
% Copyright (c) 2007 Gabriel Peyre
vertex = check_size(vertex);
face = check_size(face);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
f... |
github | jacksky64/imageProcessing-master | load_signal.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/load_signal.m | 12,338 | utf_8 | b70e4cb57d6b467ae9c90d4b3310a81f | function y = load_signal(name, n, options)
% load_signal - load a 1D signal
%
% y = load_signal(name, n, options);
%
% name is a string that can be :
% 'regular' (options.alpha gives regularity)
% 'step', 'rand',
% 'gaussiannoise' (options.sigma gives width of filtering in pixels),
% [natural signa... |
github | jacksky64/imageProcessing-master | perform_kmeans.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/perform_kmeans.m | 15,880 | utf_8 | 889e597cbf17eb5c230a7d0c9963d860 | function [B,seeds,E] = perform_kmeans(X,nbCluster,options)
% perform_kmeans - perform the k-means clustering algorithm.
%
% [B,seeds] = perform_kmeans(X,nbCluster,options);
%
% 'X' is a [d,n] matrix where d is the dimension of the space
% and n is the number of points (that live in R^d).
% 'nbClust... |
github | jacksky64/imageProcessing-master | perform_dct_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/perform_dct_transform.m | 7,750 | utf_8 | 07f7ce84cf4f6dfc91ad645a17eab05c | function y = perform_dct_transform(x,dir)
% perform_dct_transform - discrete cosine transform
%
% y = perform_dct_transform(x,dir);
%
% Copyright (c) 2006 Gabriel Peyre
if size(x,1)==1 || size(x,2)==1
% 1D transform
if dir==1
y = dct(x);
else
y = idct(x);
end
else
if dir==1
... |
github | jacksky64/imageProcessing-master | compute_skewness.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/compute_skewness.m | 2,386 | utf_8 | d4d80af526ebb3b179c6b16cd6e2a4e3 | function s = compute_skewness(x,center_mean)
% compute_skewness compute the Skewness.
% returns the sample skewness of the values in X. For a
% vector input, S is the third central moment of X, divided by the cube
% of its standard deviation. For a matrix input, S is a row vector
% containing the samp... |
github | jacksky64/imageProcessing-master | compute_kurtosis.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/compute_kurtosis.m | 2,498 | utf_8 | 36e9c2e951aed214419c3eaccfcdcf44 | function k = compute_kurtosis(x, center_mean)
%compute_kurtosis - compute the Kurtosis.
%
% returns the sample kurtosis of the values in X. For a
% vector input, K is the fourth central moment of X, divided by fourth
% power of its standard deviation. For a matrix input, K is a row vector
% containing ... |
github | jacksky64/imageProcessing-master | compute_histogram_distance.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/compute_histogram_distance.m | 1,926 | utf_8 | 8d2e4fb98f34f913571462dc3fec7fe2 | function D = compute_histogram_distance(H, options)
% compute_histogram_distance - compute distance between histograms
%
% D = compute_histogram_distance(H, options);
%
% H(:,i) is the ith histogram.
% D(i,g) is the distance between histogram i and j.
%
% options.histmetric is the metric used to compute the distan... |
github | jacksky64/imageProcessing-master | compute_histogram_rbf.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/compute_histogram_rbf.m | 2,360 | utf_8 | db90055f55a69747e4b061c873ac0365 | function h = compute_histogram_rbf(f, sigma, x, options)
% compute_histogram_rbf - parzen windows density estimation
%
% h = compute_histogram_rbf(f, sigma, x);
%
% f is the signal, h is an estimate of the histogram,
% where h(i) is the density of the estimation around value x(i).
%
% sigma is the bandwidth u... |
github | jacksky64/imageProcessing-master | compute_distance_matrix.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/compute_distance_matrix.m | 2,330 | utf_8 | 027fcf29f3d2a1b697af4bbb4d809c77 | function dist = compute_distance_matrix(X,x)
% compute_distance_matrix - compute pairwise distance matrix.
%
% D = compute_distance_matrix(X);
% or
% D = compute_distance_matrix(X,x, metric);
% (set x=X)
%
% We have D(i,j)=|X(:,i)-x(:,j)|^2.
%
% Copyright (c) 2004 Gabriel Peyre
[D,N] = size(X)... |
github | jacksky64/imageProcessing-master | mad.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/mad.m | 7,921 | utf_8 | 6d4949e64f7802d97e068c87415b0460 | function y = mad(x,flag)
%MAD Mean/median absolute deviation.
% Y = MAD(X) returns the mean absolute deviation of the values in X. For
% vector input, Y is MEAN(ABS(X-MEAN(X)). For a matrix input, Y is a row
% vector containing the mean absolute deviation of each column of X. For
% N-D arrays, MAD oper... |
github | jacksky64/imageProcessing-master | perform_moment_equalization.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/perform_moment_equalization.m | 11,991 | utf_8 | cd7ec09148f7192b3fda19ca178088e1 | function x = perform_moment_equalization(x,y,numdim, options)
% perform_kurtosis_equalization - equalize moments of order 1,2,3,4.
%
% x = perform_moment_equalization(x,y,numdim,options);
%
% (numdim=1 by default).
%
% Equalizes the mean, variance, skewness and kurtosis.
% Set options.xx=0 to avoid eq... |
github | jacksky64/imageProcessing-master | perform_histogram_matching.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/perform_histogram_matching.m | 6,400 | utf_8 | 60f90bff8d6cd335507795f1602dafad | function x = perform_histogram_matching(x, y, options)
% perform_histogram_matching - match the histogram of two image.
%
% x = perform_histogram_matching(x, y, nb_bins);
% or
% x = perform_histogram_matching(x, y, options);
%
% Perform an equalization of x so that it histogram
% matches the histogra... |
github | jacksky64/imageProcessing-master | load_image.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_signal/toolbox/load_image.m | 15,910 | utf_8 | f5a8233f70450d4ce607431750bcffda | function M = load_image(type, n, options)
% load_image - load benchmark images.
%
% M = load_image(name, n, options);
%
% name can be:
% Synthetic images:
% 'chessboard1', 'chessboard', 'square', 'squareregular', 'disk', 'diskregular', 'quaterdisk', '3contours', 'line',
% 'line_vertical', 'l... |
github | jacksky64/imageProcessing-master | perform_bregman_l1.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/perform_bregman_l1.m | 30,356 | utf_8 | 9b24d52e8a09ba53a227bc8fbc8a08d8 | function Out = perform_bregman_l1(n,A,b,mu,M,opts,varargin)
% Solve the problem
% min ||x||_1, subject to Ax = b
% by calling the solver FPC for solving multiple instances of
% min mu*||x||_1 + 0.5*||Ax-b^k||^2 .
% (FPC can be substituted by other solvers for the same subproblem)
%
% Technical Report:
% W. Yin... |
github | jacksky64/imageProcessing-master | callback_fft.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/callback_fft.m | 1,815 | utf_8 | d2cbd486232bc3f7a4a6e537092d87a1 | function y = callback_fft(x,dir,options)
% callback_fft - callback for sparsity with FFT
%
% y = callback_fft(x,dir,options);
%
% Works in 1D and 2D. Orthogonal transforms.
%
% Copyright (c) 2008 Gabriel Peyre
options.null = 0;
%% Detect dimension
if size(x,1)==1 || size(x,2)==1
ndims = 1;
else
ndims =... |
github | jacksky64/imageProcessing-master | perform_analysis_regularization.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/perform_analysis_regularization.m | 2,585 | utf_8 | c15e65a8b4b77823cd42e992ac708563 | function [g,g_list,E] = perform_analysis_regularization(f, G, options)
% perform_analysis_regularization - perform a sparse regularization
%
% [g,g_list,E] = perform_analysis_regularization(f, A, options);
%
% Method solves, given f of length n, for
% min_g E(g) = 1/2*|f-g|^2 + lambda * |A*g|_1
% where A is a... |
github | jacksky64/imageProcessing-master | perform_dictionary_learning.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/perform_dictionary_learning.m | 11,227 | utf_8 | 7d719ce3e479bb813629d6651d16f2a3 | function [D,X,E] = perform_dictionary_learning(Y,options)
% perform_dictionary_learning - learn a dictionnary using K-SVD algorithm
%
% [D,X,E] = perform_dictionary_learning(Y,options)
%
% Y is a matrix of size (n,m) containing m column examplar
% vector in R^n.
%
% D is a dictionnary matrix of size (n,K) ... |
github | jacksky64/imageProcessing-master | callback_sensing_rand.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/callback_sensing_rand.m | 8,894 | utf_8 | 903359765b01d21f154c6259c5c0c98d | function y = callback_sensing_rand(x, dir, options)
% callback_sensing_rand - perform random sensing
%
% y = callback_sensing_rand(x, dir, options);
%
% compute y=K*x (dir=1) or y=K^{*}*x (dir=-1) or y=K^{+}*x (pseudo inverse)
% where K is a random matrix.
%
% You need to set options.n and options.p... |
github | jacksky64/imageProcessing-master | compute_redundant_dictionary.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/compute_redundant_dictionary.m | 3,651 | utf_8 | 873380c9481c36f5a06629f27c1719b4 | function [D,info] = compute_redundant_dictionary(name,n,options)
% compute_redundant_dictionary - compute several redundant dictionaries (matrices)
%
% [D,info] = compute_redundant_dictionary(name,n,options);
%
% n is the dimension
% options.q controls the redundancy
% info is a struct continaining inf... |
github | jacksky64/imageProcessing-master | perform_omp.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/perform_omp.m | 9,857 | utf_8 | 84fa05746f22e0ac58735d2c53b486f1 | function X = perform_omp(D,Y,options)
% perform_omp - perform orthogonal matching pursuit
%
% X = perform_omp(D,Y,options);
%
% D is the dictionary of size (n,p) of p atoms
% Y are the m vectors to decompose of size (n,m)
% X are the m coefficients of the decomposition of size (p,m).
%
% Orthogonal matching ... |
github | jacksky64/imageProcessing-master | perform_mca.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/perform_mca.m | 6,874 | utf_8 | f5c4b3fc3e6b267294c05d8f6ec46911 | function ML = perform_mca(M, components, options)
% perform_mca - perform MCA decomposition
%
% ML = perform_mca(M, components, options);
%
% ML(:,:,i) is the layer optained by sparse decomposition in
% dictionary Di described by components{i}.
%
% components is a cell array of structure.
% cpt = com... |
github | jacksky64/imageProcessing-master | compute_synthetic_dictionary.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/compute_synthetic_dictionary.m | 5,246 | utf_8 | 30de6dc1f7a7b49db0d9b4ae9489fb86 | function D = compute_synthetic_dictionary(name, w, options)
% compute_synthetic_dictionary - compute a synthetic dictionary
%
% D = compute_synthetic_dictionary(name, w, options);
%
% w is the width of the patches.
% names is 'edges', 'oscillations', 'lines' or 'crossings'.
%
% Copyright (c) 2007 Gabriel Peyre... |
github | jacksky64/imageProcessing-master | perform_debiasing.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/perform_debiasing.m | 2,313 | utf_8 | 89cb6ddcc4c67a5af08b981e00c08149 | function [x1,err] = perform_debiasing(A,x,y, options)
% perform_debiasing - remove bias by orthogonal projection
%
% x1 = perform_debiasing(A,x,y, options);
%
% Compute x1 with same support I=find(abs(x)>Thresh) as x that minimize
% min | y - A(:,I)*x(I) |
% Thresh is set in options.Thresh
%
% Usefull to... |
github | jacksky64/imageProcessing-master | perform_windowed_fourier_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/perform_windowed_fourier_transform.m | 5,038 | utf_8 | 96c27071ef4e8304b6051ed54d7ad8b8 | function y = perform_windowed_fourier_transform(x,w,q,n, options)
% perform_windowed_fourier_transform - compute a local Fourier transform
%
% Forward transform:
% MF = perform_windowed_fourier_transform(M,w,q,n, options);
% Backward transform:
% M = perform_windowed_fourier_transform(MF,w,q,n, options);
%
% w ... |
github | jacksky64/imageProcessing-master | load_image.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/load_image.m | 15,910 | utf_8 | f5a8233f70450d4ce607431750bcffda | function M = load_image(type, n, options)
% load_image - load benchmark images.
%
% M = load_image(name, n, options);
%
% name can be:
% Synthetic images:
% 'chessboard1', 'chessboard', 'square', 'squareregular', 'disk', 'diskregular', 'quaterdisk', '3contours', 'line',
% 'line_vertical', 'l... |
github | jacksky64/imageProcessing-master | grab_inpainting_mask.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/grab_inpainting_mask.m | 3,553 | utf_8 | e1b2c4077e57645a8b91a2bc47fd1245 | function [U,point_list] = grab_inpainting_mask(M, options, mode)
% grab_inpainting_mask - create a mask from user input
%
% U = grab_inpainting_mask(M, options);
%
% options.r is the radius for selection (default r=5).
%
% Selection stops with right click.
%
% Copyright (c) 2006 Gabriel Peyre
if nargin==3 &&... |
github | jacksky64/imageProcessing-master | perform_atrou_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/perform_atrou_transform.m | 23,360 | utf_8 | ff914c13e923fce2f63396a7faa47d26 | function y = perform_atrou_transform(x,Jmin,options)
% perform_atrou_transform - compute the "a trou" wavelet transform,
% i.e. without subsampling.
%
% w_list = perform_atrou_transform(M,Jmin,options);
%
% 'w_list' is a cell array, w_list{ 3*(j-Jmin)+q }
% is an imagette of same size as M containing ... |
github | jacksky64/imageProcessing-master | perform_dct_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/perform_dct_transform.m | 7,750 | utf_8 | 07f7ce84cf4f6dfc91ad645a17eab05c | function y = perform_dct_transform(x,dir)
% perform_dct_transform - discrete cosine transform
%
% y = perform_dct_transform(x,dir);
%
% Copyright (c) 2006 Gabriel Peyre
if size(x,1)==1 || size(x,2)==1
% 1D transform
if dir==1
y = dct(x);
else
y = idct(x);
end
else
if dir==1
... |
github | jacksky64/imageProcessing-master | perform_thresholding.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/perform_thresholding.m | 2,482 | utf_8 | 0f3a43687bf3809b0789cace4871a1e6 | function y = perform_thresholding(x, t, type)
% perform_thresholding - perform hard or soft thresholding
%
% y = perform_thresholding(x, t, type);
%
% type is either 'hard' or 'soft' or 'semisoft'
% t is the threshold
%
% works also for complex data, and for cell arrays.
%
% if type is 'strict' then it keeps... |
github | jacksky64/imageProcessing-master | cgsolve.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/cgsolve.m | 1,626 | utf_8 | 144fb53044ae853bc0d1d7f6cf8f8f3d | % cgsolve.m
%
% Solve a symmetric positive definite system Ax = b via conjugate gradients.
%
% Usage: [x, res, iter] = cgsolve(A, b, tol, maxiter, verbose)
%
% A - Either an NxN matrix, or a function handle.
%
% b - N vector
%
% tol - Desired precision. Algorithm terminates when
% norm(Ax-b)/norm(b) < tol .
%
% ma... |
github | jacksky64/imageProcessing-master | SolveOMP.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/SolveOMP.m | 5,517 | utf_8 | f4e04a5fa97a57fc5a3f3cebae686a5e | function [sols, iters, activationHist] = SolveOMP(A, y, N, maxIters, lambdaStop, solFreq, verbose, OptTol)
% SolveOMP: Orthogonal Matching Pursuit
% Usage
% [sols, iters, activationHist] = SolveOMP(A, y, N, maxIters, lambdaStop, solFreq, verbose, OptTol)
% Input
% A Either an explicit nxN matrix, with ra... |
github | jacksky64/imageProcessing-master | l1eq_pd.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/l1eq_pd.m | 5,308 | utf_8 | c2d14a529c067d730ebee8140ec5ecc4 | % l1eq_pd.m
%
% Solve
% min_x ||x||_1 s.t. Ax = b
%
% Recast as linear program
% min_{x,u} sum(u) s.t. -u <= x <= u, Ax=b
% and use primal-dual interior point method
%
% Usage: xp = l1eq_pd(x0, A, At, b, pdtol, pdmaxiter, cgtol, cgmaxiter)
%
% x0 - Nx1 vector, initial point.
%
% A - Either a handle to a function t... |
github | jacksky64/imageProcessing-master | perform_tv_correction.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/perform_tv_correction.m | 985 | utf_8 | e9637dd038c9c859b0c6dedd242fecae | function y = perform_tv_correction(x,T)
% perform_tv_correction - perform correction of the image to that it minimizes the TV norm.
%
% y = perform_tv_correction(x,T);
%
% Perform correction using thresholding of haar wavelet coefficients on 1
% scale.
%
% Copyright (c) 2006 Gabriel Peyre
n = size(x,1);
Jmin ... |
github | jacksky64/imageProcessing-master | perform_windowed_dct_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/perform_windowed_dct_transform.m | 2,282 | utf_8 | 9c456075e56465427a4442c1e5c9afc8 | function y = perform_windowed_dct_transform(x,w,q,n, options)
% perform_windowed_dct_transform - compute a local DCT transform
%
% Forward transform:
% MF = perform_windowed_dct_transform(M,w,q,n, options);
% Backward transform:
% M = perform_windowed_dct_transform(MF,w,q,n, options);
%
% w is the width of the ... |
github | jacksky64/imageProcessing-master | mad.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/mad.m | 7,921 | utf_8 | 6d4949e64f7802d97e068c87415b0460 | function y = mad(x,flag)
%MAD Mean/median absolute deviation.
% Y = MAD(X) returns the mean absolute deviation of the values in X. For
% vector input, Y is MEAN(ABS(X-MEAN(X)). For a matrix input, Y is a row
% vector containing the mean absolute deviation of each column of X. For
% N-D arrays, MAD oper... |
github | jacksky64/imageProcessing-master | perform_wavelet_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/perform_wavelet_transform.m | 61,619 | utf_8 | 9e8ee118ad0e2225d236b242630cc67a | function y = perform_wavelet_transform(x, Jmin, dir, options)
% perform_wavelet_transform - wrapper to wavelab Wavelet transform (1D/2D and orthogonal/biorthogonal).
%
% y = perform_wavelet_transform(x, Jmin, dir, options);
%
% 'x' is either a 1D or a 2D array.
% 'Jmin' is the minimum scale (i.e. the coar... |
github | jacksky64/imageProcessing-master | pdco.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_sparsity/toolbox/pdco.m | 54,786 | utf_8 | 24b840a986d1c21cadf453a476c677e6 | function [x,y,z,inform,PDitns,CGitns,time] = ...
pdco( Fname,Aname,b,bl,bu,d1,d2,options,x0,y0,z0,xsize,zsize )
%-----------------------------------------------------------------------
% pdco.m: Primal-Dual Barrier Method for Convex Objectives (23 Sep 2003)
%--------------------------------------------------------... |
github | jacksky64/imageProcessing-master | perform_lifting_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_lifting_transform.m | 5,259 | utf_8 | 10f0ac03e72e5bb21bb572abfb21eceb | function x = perform_lifting_transform(x, Jmin, dir, options)
% perform_lifting_transform - peform fast lifting transform
%
% y = perform_lifting_transform(x, Jmin, dir, options);
%
% Implement 1D and 2D symmetric wavelets with symmetric boundary treatements, using
% a lifting implementation.
%
% h = ... |
github | jacksky64/imageProcessing-master | perform_wavelet_matching.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_wavelet_matching.m | 5,655 | utf_8 | ce80d6388fa6824a0f269c8a29c4f023 | function [M1,MW,MW1] = perform_wavelet_matching(M1,M,options)
% perform_wavelet_matching - match multiscale histograms
%
% M1 = perform_wavelet_matching(M1,M,options);
%
% M1 is the image to synthesize.
% M is the exemplar image.
%
% This function match the histogram of the image and the histogram
% of each s... |
github | jacksky64/imageProcessing-master | perform_quicunx_wavelet_transform_ti.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_quicunx_wavelet_transform_ti.m | 3,927 | utf_8 | b81d7eec362739361304b4e77817f9d6 | function M = perform_quicunx_wavelet_transform_ti(M,Jmin,options)
% perform_quicunx_wavelet_transform_ti - translation invariant quincunx wavelets
%
% Forward
% MW = perform_quicunx_wavelet_transform_ti(M,Jmin,options);
% Backward
% M = perform_quicunx_wavelet_transform_ti(MW,Jmin,options);
%
% The implementatio... |
github | jacksky64/imageProcessing-master | perform_curvelet_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_curvelet_transform.m | 33,957 | utf_8 | 63811c4cedefc4b0a5ede5a2b3269c54 | function y = perform_curvelet_transform(x,options)
% perform_curvelet_transform - a wrapper to curvlab
%
% M = perform_curvelet_transform(MW,options);
%
% Forward and backward curvelet transform
% You must provide options.n (width of the image).
%
% Visit www.curvelab.org for the full code.
optio... |
github | jacksky64/imageProcessing-master | perform_atrou_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_atrou_transform.m | 23,527 | utf_8 | 4cde4e609d6784e61c27a06afbba626b | function y = perform_atrou_transform(x,Jmin,options)
% perform_atrou_transform - compute the "a trou" wavelet transform,
%
% This function is depreciated, use perform_wavelet_transform instead.
%
% Copyright (c) 2006 Gabriel Peyre
% w_list = perform_atrou_transform(M,Jmin,options);
%
% 'w_list' is ... |
github | jacksky64/imageProcessing-master | perform_spiht_coding.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_spiht_coding.m | 16,676 | utf_8 | 887f72ff117400ec78d7f4bd15f07015 | function [y,nbr_bits] = perform_spiht_coding(x,options)
% perform_spiht_coding - SPIHT coding of wavelet coefficients
%
% Coding :
% options.Jmin = ??; % minimum scale of the transform
% options.nb_bits = ??; % target number of bits
% [stream,nbr_bits] = perform_spiht_coding(MW,options);
% Decodi... |
github | jacksky64/imageProcessing-master | perform_blsgsm_denoising.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_blsgsm_denoising.m | 41,741 | utf_8 | d7adcb441f0d91f470957d7d1083332f | function y = perform_blsgsm_denoising(x, options)
% perform_blsgsm_denoising - denoise an image using BLS-GSM
%
% y = perform_blsgsm_denoising(x, options);
%
% BLS-GSM stands for "Bayesian Least Squares - Gaussian Scale Mixture".
%
% This function is a wrapper for the code of J.Portilla.
%
% You can change the ... |
github | jacksky64/imageProcessing-master | perform_segmentation.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_segmentation.m | 5,024 | utf_8 | 838e39d3911cf7fa55e00ec1a6c11952 | function [B,err] = perform_segmentation(E,options)
% perform_segmentation - perform image segmentation
%
% B = perform_segmentation(E,options);
%
% E is an (n,n,k) set of k dimensional features vectors (one per pixel in
% the image).
%
% options.segmentation_method can be
% 'simple': E(:,:,k) should be ... |
github | jacksky64/imageProcessing-master | perform_histogram_matching_wavelet.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_histogram_matching_wavelet.m | 4,495 | utf_8 | 2583a784c610f9a09bd02673493e83f1 | function MW_src = perform_histogram_matching_wavelet(MW_src,MW_tgt, Jmin, options)
% perform_histogram_matching_wavelet - match the histogram of a wavelet transform
%
% Matching of wavelet coefficients only:
% options.dotransform=0
% MW_src = perform_histogram_matching_wavelet(MW_src,MW_tgt,Jmin,options);
%... |
github | jacksky64/imageProcessing-master | perform_steerable_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_steerable_transform.m | 62,306 | utf_8 | 8682ba128191ecc103c6b02364081a6e | function y = perform_steerable_transform(x, Jmin,options)
% perform_steerable_transform - steerable pyramidal transform
%
% y = perform_steerable_transform(x, Jmin,options);
%
% This is just a convenient wrapper to the original steerable
% matlab toolbox of Simoncelli that can be downloaded from
% ... |
github | jacksky64/imageProcessing-master | perform_quincunx_wavelet_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_quincunx_wavelet_transform.m | 23,730 | utf_8 | 1adf6e891e72693338d272d2f7c03be8 | function [y,quincunx_filters] = perform_quincunx_wavelet_transform(x,Jmin,dir,options)
% perform_quincunx_wavelet_transform - compute quincunx transform
%
% Forward transform
% [MW,options.quincunx_filters] = perform_quincunx_wavelet_transform(M,Jmin,+1,options);
% Backward transform
% M = perform_quincunx_... |
github | jacksky64/imageProcessing-master | perform_waveatoms_transform.m | .m | imageProcessing-master/Matlab imaging/Matlab toolbox/toolbox_wavelets/perform_waveatoms_transform.m | 24,620 | utf_8 | a14b7c361a63a2e3e55c96f6fbb09d09 | function y = perform_waveatoms_transform(x,dir, options)
% perform_waveatoms_transform - interface to WaveAtom transform
%
% y = perform_waveatoms_transform(x,dir, options);
%
% The waveatom toolbox can be downloaded from
% http://www.waveatom.org/
%
% Copyright (c) 2007 Gabriel Peyre
options.null = 0;
is... |
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