This library collects various image processing algorithms and provides simple access to them. All algorithms are implemented in Java and runs without any other dependencies. Some algorithms are pretty standard and others maybe do you know from Photoshop. It starts with less basic features and grow over the last years. If you need high power performance better use opencv for processing.
If you like this project and you want to keep me awake 🤪
If you want to use this library in your processing sketch you can download it via the integrated Contribution Manager.
The following algorithms are supported in this library. Click on the link to see an example image and a code snippet.
Photo taken by me more here
PImage processedImage = Grayscale.apply(image);
PImage processedImage = Flip.apply(image, horizontal, vertical); // horizontal and vertical are boolean
// invertRed, invertGreen and invertBlue are boolean
PImage processedImage = InvertColors.apply(image, invertRed, invertGreen, invertBlue); 
PImage processedImage = Threshold.apply(image); // Auto threshold
PImage processedImage = Threshold.apply(image, value); // Threshold value between 0 and 255
PImage processedImage = Dilation.apply(image, radius); // radius is a positive number
PImage processedImage = Erosion.apply(image, radius); // radius is a positive number
// intensity and vignetteWidth are floats between 0.0 and 1.0
PImage processedImage = Vignette.apply(image, intensity, vignetteWidth); 
PImage processedImage = Quantization.apply(image, shades); // shades is a positive number between 1 and 255
PImage processedImage = PaletteMapping.apply(image, color1, color2, color3); // Add any number of colors from dark to light
// difference is a float between 0.0 and 1.0 from less to very different
float difference = Comparison.howDifferent(image1, image2);
// differenceImage is the difference between the pixel values (black is no difference, white is high difference)
PImage differenceImage = Comparison.calculateDifferenceImage(image1, image2);
PImage processedImage = Gaussian.apply(image, 7, 0.84089642); // kernel size and sigma 
// pixelsize is a positive number
PImage processedImage = Pixelation.apply(image, pixelsize);
// Pixelize a sub area of the input image
PImage processedImage = Pixelation.apply(image, pixelsize, subX, subY, subWidth, subHeight); 
PImage processedImage = TiltShift.apply(image, blurIntensity, horizontal, position, sharpWideness); 
PImage processedImage = CannyEdgeDetector.apply(image);
PImage processedImage = SobelEdgeDetector.apply(image);
// for colored sobel (for each color channel)
PImage processedImage = SobelEdgeDetector.apply(image, false);
PImage processedImage = Brightness.apply(image, value);
// value isa positive number for brighting up or a negative for darken down
// intensity is between -1.0 and 1.0
PImage processedImage = Contrast.apply(image, intensity); 
// intensity is between 0.0 and 10.0
// 0.0 to 1.0 decreases and all above increases the saturation
PImage processedImage = Saturation.apply(image, intensity); 
// intensity between -1.0 and 1.0
PImage processedImage = Lights.apply(image, intensity); 
// intensity between -1.0 and 1.0
PImage processedImage = Shadows.apply(image, intensity); 
PImage processedImage = AutoBalance.apply(image);
PImage processedImage = Bloom.apply(image, intensity); // intensity between 0 and 255
PImage processedImage = Sharpen.apply(image, sharpIntensity); // sharpIntensity between 0.0 and 10.0
// hue is a value between 0 and 360
// offset is the color range which is accepted (in hue range)
// shift is the number of the subtracted or added hue value
PImage processedImage = ColorShift.applyHue(image, hue, offset, shift); // or short: ColorShift.apply(image, hue, offset, shift)
PImage processedImage = ColorShift.applySaturation(image, hue, offset, shift);
PImage processedImage = ColorShift.applyBrightness(image, hue, offset, shift);
LUT style = LUT.loadLut(LUT.STYLE.CONTRAST);
PImage processedImage = LUT.apply(image, style); 
PImage processedImage = RetroConsole.applyGameboy(image, pixelSize); 
PImage processedImage = Glitch.apply(image, intensity, scanlineheight);
PImage processedImage = Matte.apply(image,
matteIntensity, // intensity for the lifting blacks between 0 and 255
contrastIntensity, // intensity for the constrast between 0 and 255
saturationIntensity); // change for the saturation between -0.5 and 0.5
// intensity between 0.0 and 1.0
PImage processedImage = Sabattier.apply(image, intensity);
PImage processedImage = Sabattier.applyRed(image, intensity);
PImage processedImage = Sabattier.applyGreen(image, intensity);
PImage processedImage = Sabattier.applyBlue(image, intensity);| random angles | fixed angle |
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PImage processedImage = Strokes.apply(image, gridSize, lineLength);
PImage processedImage = Strokes.apply(image,
gridSize, // is positive and the area for compound pixels
lineLength, // is positive and the length in pixels for each line
lineWeight, // is positive and the weight of each line in pixel
linesPerGrid, // the number of lines per grid
lineIntensity, // alpha value for each line between 0 and 255
degree, // if set the rotation is fixed in degree, otherwise random
inColor, // true for colors else black and white
backgroundColor); // color for the background
// default dithering algorithm is BAYER_4x4
PImage processedImage = Dithering.apply(image);
// change algrithm: BAYER_2x2, BAYER_4x4, BAYER_8x8
PImage processedImage = Dithering.apply(image, Dithering.Algorithm.BAYER_8x8);
// use a curstom kernel (kernel = float[])
PImage processedImage = Dithering.aapply(PImage image, kernel); 
PImage processedImage = Halftone.apply(image, dotsize); // dot size in pixel
PImage processedImage = Halftone.apply(image, dotsize, grid); // grid = true, on false honeycomb style
PImage processedImage = Halftone.apply(image, dotsize, foreground, background); // background and foreground colors
PImage processedImage = Halftone.apply(image, dotsize, foreground, background, grid);
PImage processedImage = Halftone.apply(image, dotsize, foreground, background, spacing, grid); // size between dots in pixels
// tone is a color and intensity is a value between 0.0 and 1.0
color tone = color(255, 11, 120);
float intensity = 0.8f;
PImage processedImage = Toning.apply(image, tone, intensity);
PImage processedImage = SplitToning.apply(
image,
highlightTone, // Color for highlighs (f.e. color highlightTone = color(211, 180, 21);
intensityHighlights, // intensity for the toning in highlights between 0.0 and 1.0
shadowTone, // Color for the shadows (f.e. color shadowTone = color(124, 32, 201);
intensityShadows); // intensity for the toning in the shadows between 0.0 and 1.0
PImage processedImage = SineWave.apply(image, rowHeight, weight, backgroundColor, wavesColor);
// keeps the original colors
PImage processedImage = Knitting.apply(image, size);
// Sets foreground and background color and uses a threshold
PImage processedImage = Knitting.apply(image, size, threshold, 240, #EE0000); 
PImage processedImage = ASCII.apply(image);
// characterset = ASCII.SHORT_SET or ASCII.LONG_SET, another String from black to white
PImage processedImage = ASCII.apply(image, characterset);
PImage processedImage = ASCII.apply(image, characterset, fontSize); // fontSize is an integer
PImage processedImage = ASCII.apply(image, characterset, fontSize, foregroundColor, backgroundColor, toneInColor);
// To get the ASCII image as plain string use the following method
PImage processedImage = ASCII.getAsciiText(image); 
// Add so many images in the end as you need
PImage processedImage = Stacker.apply(Stacker.ALGORITHM.AVERAGE, image1, image2);
PImage processedImage = Stacker.apply(Stacker.ALGORITHM.MEDIAN, image1, image2);
// intensity is a float between 0.0 and 1.0
PImage processedImage = Blend.apply(image1, image2, intensity);My special thanks goes to avatarr for implementing and publishing basic algorithms. Also thank you very much Tom Gibara for your great blog post and the implementation of the canny edge detector.
Moreover I thank you Joseph HENRY for the Sine-Wave-effect code and uheinema for the Sabattier code in the Processing Discourse.