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// SPDX-License-Identifier: Apache-2.0
#include <algorithm>
#include <functional>
#include <memory>
#include <tuple>
#include <vector>
#include <vips/vips8>
#include "common.h"
#include "operations.h"
using vips::VImage;
using vips::VError;
namespace sharp {
/*
* Tint an image using the provided RGB.
*/
VImage Tint(VImage image, std::vector<double> const tint) {
std::vector<double> const tintLab = (VImage::black(1, 1) + tint)
.colourspace(VIPS_INTERPRETATION_LAB, VImage::option()->set("source_space", VIPS_INTERPRETATION_sRGB))
.getpoint(0, 0);
// LAB identity function
VImage identityLab = VImage::identity(VImage::option()->set("bands", 3))
.colourspace(VIPS_INTERPRETATION_LAB, VImage::option()->set("source_space", VIPS_INTERPRETATION_sRGB));
// Scale luminance range, 0.0 to 1.0
VImage l = identityLab[0] / 100;
// Weighting functions
VImage weightL = 1.0 - 4.0 * ((l - 0.5) * (l - 0.5));
VImage weightAB = (weightL * tintLab).extract_band(1, VImage::option()->set("n", 2));
identityLab = identityLab[0].bandjoin(weightAB);
// Convert lookup table to sRGB
VImage lut = identityLab.colourspace(VIPS_INTERPRETATION_sRGB,
VImage::option()->set("source_space", VIPS_INTERPRETATION_LAB));
// Original colourspace
VipsInterpretation typeBeforeTint = image.interpretation();
if (typeBeforeTint == VIPS_INTERPRETATION_RGB) {
typeBeforeTint = VIPS_INTERPRETATION_sRGB;
}
// Apply lookup table
if (HasAlpha(image)) {
VImage alpha = image[image.bands() - 1];
image = RemoveAlpha(image)
.colourspace(VIPS_INTERPRETATION_B_W)
.maplut(lut)
.colourspace(typeBeforeTint)
.bandjoin(alpha);
} else {
image = image
.colourspace(VIPS_INTERPRETATION_B_W)
.maplut(lut)
.colourspace(typeBeforeTint);
}
return image;
}
/*
* Stretch luminance to cover full dynamic range.
*/
VImage Normalise(VImage image, int const lower, int const upper) {
// Get original colourspace
VipsInterpretation typeBeforeNormalize = image.interpretation();
if (typeBeforeNormalize == VIPS_INTERPRETATION_RGB) {
typeBeforeNormalize = VIPS_INTERPRETATION_sRGB;
}
// Convert to LAB colourspace
VImage lab = image.colourspace(VIPS_INTERPRETATION_LAB);
// Extract luminance
VImage luminance = lab[0];
// Find luminance range
int const min = lower == 0 ? luminance.min() : luminance.percent(lower);
int const max = upper == 100 ? luminance.max() : luminance.percent(upper);
if (std::abs(max - min) > 1) {
// Extract chroma
VImage chroma = lab.extract_band(1, VImage::option()->set("n", 2));
// Calculate multiplication factor and addition
double f = 100.0 / (max - min);
double a = -(min * f);
// Scale luminance, join to chroma, convert back to original colourspace
VImage normalized = luminance.linear(f, a).bandjoin(chroma).colourspace(typeBeforeNormalize);
// Attach original alpha channel, if any
if (HasAlpha(image)) {
// Extract original alpha channel
VImage alpha = image[image.bands() - 1];
// Join alpha channel to normalised image
return normalized.bandjoin(alpha);
} else {
return normalized;
}
}
return image;
}
/*
* Contrast limiting adapative histogram equalization (CLAHE)
*/
VImage Clahe(VImage image, int const width, int const height, int const maxSlope) {
return image.hist_local(width, height, VImage::option()->set("max_slope", maxSlope));
}
/*
* Gamma encoding/decoding
*/
VImage Gamma(VImage image, double const exponent) {
if (HasAlpha(image)) {
// Separate alpha channel
VImage alpha = image[image.bands() - 1];
return RemoveAlpha(image).gamma(VImage::option()->set("exponent", exponent)).bandjoin(alpha);
} else {
return image.gamma(VImage::option()->set("exponent", exponent));
}
}
/*
* Flatten image to remove alpha channel
*/
VImage Flatten(VImage image, std::vector<double> flattenBackground) {
double const multiplier = sharp::Is16Bit(image.interpretation()) ? 256.0 : 1.0;
std::vector<double> background {
flattenBackground[0] * multiplier,
flattenBackground[1] * multiplier,
flattenBackground[2] * multiplier
};
return image.flatten(VImage::option()->set("background", background));
}
/**
* Produce the "negative" of the image.
*/
VImage Negate(VImage image, bool const negateAlpha) {
if (HasAlpha(image) && !negateAlpha) {
// Separate alpha channel
VImage alpha = image[image.bands() - 1];
return RemoveAlpha(image).invert().bandjoin(alpha);
} else {
return image.invert();
}
}
/*
* Gaussian blur. Use sigma of -1.0 for fast blur.
*/
VImage Blur(VImage image, double const sigma, VipsPrecision precision, double const minAmpl) {
if (sigma == -1.0) {
// Fast, mild blur - averages neighbouring pixels
VImage blur = VImage::new_matrixv(3, 3,
1.0, 1.0, 1.0,
1.0, 1.0, 1.0,
1.0, 1.0, 1.0);
blur.set("scale", 9.0);
return image.conv(blur);
} else {
// Slower, accurate Gaussian blur
return StaySequential(image).gaussblur(sigma, VImage::option()
->set("precision", precision)
->set("min_ampl", minAmpl));
}
}
/*
* Convolution with a kernel.
*/
VImage Convolve(VImage image, int const width, int const height,
double const scale, double const offset,
std::vector<double> const &kernel_v
) {
VImage kernel = VImage::new_from_memory(
static_cast<void*>(const_cast<double*>(kernel_v.data())),
width * height * sizeof(double),
width,
height,
1,
VIPS_FORMAT_DOUBLE);
kernel.set("scale", scale);
kernel.set("offset", offset);
return image.conv(kernel);
}
/*
* Recomb with a Matrix of the given bands/channel size.
* Eg. RGB will be a 3x3 matrix.
*/
VImage Recomb(VImage image, std::vector<double> const& matrix) {
double* m = const_cast<double*>(matrix.data());
image = image.colourspace(VIPS_INTERPRETATION_sRGB);
if (matrix.size() == 9) {
return image
.recomb(image.bands() == 3
? VImage::new_matrix(3, 3, m, 9)
: VImage::new_matrixv(4, 4,
m[0], m[1], m[2], 0.0,
m[3], m[4], m[5], 0.0,
m[6], m[7], m[8], 0.0,
0.0, 0.0, 0.0, 1.0));
} else {
return image.recomb(VImage::new_matrix(4, 4, m, 16));
}
}
VImage Modulate(VImage image, double const brightness, double const saturation,
int const hue, double const lightness) {
VipsInterpretation colourspaceBeforeModulate = image.interpretation();
if (HasAlpha(image)) {
// Separate alpha channel
VImage alpha = image[image.bands() - 1];
return RemoveAlpha(image)
.colourspace(VIPS_INTERPRETATION_LCH)
.linear(
{ brightness, saturation, 1},
{ lightness, 0.0, static_cast<double>(hue) }
)
.colourspace(colourspaceBeforeModulate)
.bandjoin(alpha);
} else {
return image
.colourspace(VIPS_INTERPRETATION_LCH)
.linear(
{ brightness, saturation, 1 },
{ lightness, 0.0, static_cast<double>(hue) }
)
.colourspace(colourspaceBeforeModulate);
}
}
/*
* Sharpen flat and jagged areas. Use sigma of -1.0 for fast sharpen.
*/
VImage Sharpen(VImage image, double const sigma, double const m1, double const m2,
double const x1, double const y2, double const y3) {
if (sigma == -1.0) {
// Fast, mild sharpen
VImage sharpen = VImage::new_matrixv(3, 3,
-1.0, -1.0, -1.0,
-1.0, 32.0, -1.0,
-1.0, -1.0, -1.0);
sharpen.set("scale", 24.0);
return image.conv(sharpen);
} else {
// Slow, accurate sharpen in LAB colour space, with control over flat vs jagged areas
VipsInterpretation colourspaceBeforeSharpen = image.interpretation();
if (colourspaceBeforeSharpen == VIPS_INTERPRETATION_RGB) {
colourspaceBeforeSharpen = VIPS_INTERPRETATION_sRGB;
}
return image
.sharpen(VImage::option()
->set("sigma", sigma)
->set("m1", m1)
->set("m2", m2)
->set("x1", x1)
->set("y2", y2)
->set("y3", y3))
.colourspace(colourspaceBeforeSharpen);
}
}
VImage Threshold(VImage image, double const threshold, bool const thresholdGrayscale) {
if (!thresholdGrayscale) {
return image >= threshold;
}
return image.colourspace(VIPS_INTERPRETATION_B_W) >= threshold;
}
/*
Perform boolean/bitwise operation on image color channels - results in one channel image
*/
VImage Bandbool(VImage image, VipsOperationBoolean const boolean) {
image = image.bandbool(boolean);
return image.copy(VImage::option()->set("interpretation", VIPS_INTERPRETATION_B_W));
}
/*
Perform bitwise boolean operation between images
*/
VImage Boolean(VImage image, VImage imageR, VipsOperationBoolean const boolean) {
return image.boolean(imageR, boolean);
}
/*
Trim an image
*/
VImage Trim(VImage image, std::vector<double> background, double threshold, bool const lineArt) {
if (image.width() < 3 && image.height() < 3) {
throw VError("Image to trim must be at least 3x3 pixels");
}
if (background.size() == 0) {
// Top-left pixel provides the default background colour if none is given
background = image.extract_area(0, 0, 1, 1)(0, 0);
} else if (sharp::Is16Bit(image.interpretation())) {
for (size_t i = 0; i < background.size(); i++) {
background[i] *= 256.0;
}
threshold *= 256.0;
}
std::vector<double> backgroundAlpha({ background.back() });
if (HasAlpha(image)) {
background.pop_back();
} else {
background.resize(image.bands());
}
int left, top, width, height;
left = image.find_trim(&top, &width, &height, VImage::option()
->set("background", background)
->set("line_art", lineArt)
->set("threshold", threshold));
if (HasAlpha(image)) {
// Search alpha channel (A)
int leftA, topA, widthA, heightA;
VImage alpha = image[image.bands() - 1];
leftA = alpha.find_trim(&topA, &widthA, &heightA, VImage::option()
->set("background", backgroundAlpha)
->set("line_art", lineArt)
->set("threshold", threshold));
if (widthA > 0 && heightA > 0) {
if (width > 0 && height > 0) {
// Combined bounding box (B)
int const leftB = std::min(left, leftA);
int const topB = std::min(top, topA);
int const widthB = std::max(left + width, leftA + widthA) - leftB;
int const heightB = std::max(top + height, topA + heightA) - topB;
return image.extract_area(leftB, topB, widthB, heightB);
} else {
// Use alpha only
return image.extract_area(leftA, topA, widthA, heightA);
}
}
}
if (width > 0 && height > 0) {
return image.extract_area(left, top, width, height);
}
return image;
}
/*
* Calculate (a * in + b)
*/
VImage Linear(VImage image, std::vector<double> const a, std::vector<double> const b) {
size_t const bands = static_cast<size_t>(image.bands());
if (a.size() > bands) {
throw VError("Band expansion using linear is unsupported");
}
bool const uchar = !Is16Bit(image.interpretation());
if (HasAlpha(image) && a.size() != bands && (a.size() == 1 || a.size() == bands - 1 || bands - 1 == 1)) {
// Separate alpha channel
VImage alpha = image[bands - 1];
return RemoveAlpha(image).linear(a, b, VImage::option()->set("uchar", uchar)).bandjoin(alpha);
} else {
return image.linear(a, b, VImage::option()->set("uchar", uchar));
}
}
/*
* Unflatten
*/
VImage Unflatten(VImage image) {
if (HasAlpha(image)) {
VImage alpha = image[image.bands() - 1];
VImage noAlpha = RemoveAlpha(image);
return noAlpha.bandjoin(alpha & (noAlpha.colourspace(VIPS_INTERPRETATION_B_W) < 255));
} else {
return image.bandjoin(image.colourspace(VIPS_INTERPRETATION_B_W) < 255);
}
}
/*
* Ensure the image is in a given colourspace
*/
VImage EnsureColourspace(VImage image, VipsInterpretation colourspace) {
if (colourspace != VIPS_INTERPRETATION_LAST && image.interpretation() != colourspace) {
image = image.colourspace(colourspace,
VImage::option()->set("source_space", image.interpretation()));
}
return image;
}
/*
* Split and crop each frame, reassemble, and update pageHeight.
*/
VImage CropMultiPage(VImage image, int left, int top, int width, int height,
int nPages, int *pageHeight) {
if (top == 0 && height == *pageHeight) {
// Fast path; no need to adjust the height of the multi-page image
return image.extract_area(left, 0, width, image.height());
} else {
std::vector<VImage> pages;
pages.reserve(nPages);
// Split the image into cropped frames
image = StaySequential(image);
for (int i = 0; i < nPages; i++) {
pages.push_back(
image.extract_area(left, *pageHeight * i + top, width, height));
}
// Reassemble the frames into a tall, thin image
VImage assembled = VImage::arrayjoin(pages,
VImage::option()->set("across", 1));
// Update the page height
*pageHeight = height;
return assembled;
}
}
/*
* Split into frames, embed each frame, reassemble, and update pageHeight.
*/
VImage EmbedMultiPage(VImage image, int left, int top, int width, int height,
VipsExtend extendWith, std::vector<double> background, int nPages, int *pageHeight) {
if (top == 0 && height == *pageHeight) {
// Fast path; no need to adjust the height of the multi-page image
return image.embed(left, 0, width, image.height(), VImage::option()
->set("extend", extendWith)
->set("background", background));
} else if (left == 0 && width == image.width()) {
// Fast path; no need to adjust the width of the multi-page image
std::vector<VImage> pages;
pages.reserve(nPages);
// Rearrange the tall image into a vertical grid
image = image.grid(*pageHeight, nPages, 1);
// Do the embed on the wide image
image = image.embed(0, top, image.width(), height, VImage::option()
->set("extend", extendWith)
->set("background", background));
// Split the wide image into frames
for (int i = 0; i < nPages; i++) {
pages.push_back(
image.extract_area(width * i, 0, width, height));
}
// Reassemble the frames into a tall, thin image
VImage assembled = VImage::arrayjoin(pages,
VImage::option()->set("across", 1));
// Update the page height
*pageHeight = height;
return assembled;
} else {
std::vector<VImage> pages;
pages.reserve(nPages);
// Split the image into frames
for (int i = 0; i < nPages; i++) {
pages.push_back(
image.extract_area(0, *pageHeight * i, image.width(), *pageHeight));
}
// Embed each frame in the target size
for (int i = 0; i < nPages; i++) {
pages[i] = pages[i].embed(left, top, width, height, VImage::option()
->set("extend", extendWith)
->set("background", background));
}
// Reassemble the frames into a tall, thin image
VImage assembled = VImage::arrayjoin(pages,
VImage::option()->set("across", 1));
// Update the page height
*pageHeight = height;
return assembled;
}
}
} // namespace sharp
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