Image processing for Processing

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 🤪

Installation

If you want to use this library in your processing sketch you can download it via the integrated Contribution Manager.

Examples

Overview

The following algorithms are supported in this library. Click on the link to see an example image and a code snippet.

• Basics
  • Grayscale
  • Flip
  • Invert
  • Threshold
  • Dilation
  • Erosion
  • Vignette
  • Quantization
  • PaletteMapping
  • Difference
• Blur
  • Gaussian
  • Pixelize
  • Tilt-Shift-Effect
• Edge detection
  • Canny
  • Sobel
• Optimisation
  • Brightness
  • Contrast
  • Saturation
  • Changing highlights
  • Changing shadows
  • Auto balance
  • Bloom-Effect
  • Sharpen
  • Color-Shift
• Looks
  • Lookup table (LUT)
  • RetroConsole effect (Gameboy)
  • Glitch-Effect
  • Matte-Effect
  • Sabattier-Effect
  • Strokes
  • Dithering
  • Halftone
  • Toning
  • Split-Toning
  • Sine-Wave
  • Knitting
  • ASCII
• Miscellaneous
  • Stacked images
  • Blending images

Original image

Photo taken by me more here

Basics

Grayscale image

PImage processedImage = Grayscale.apply(image);

Flip image

PImage processedImage = Flip.apply(image, horizontal, vertical);  // horizontal and vertical are boolean

Invert colors

// invertRed, invertGreen and invertBlue are boolean
PImage processedImage = InvertColors.apply(image, invertRed, invertGreen, invertBlue);  

Threshold image

PImage processedImage = Threshold.apply(image);  // Auto threshold
PImage processedImage = Threshold.apply(image, value);  // Threshold value between 0 and 255

Dilation image

PImage processedImage = Dilation.apply(image, radius);  // radius is a positive number

Erosion image

PImage processedImage = Erosion.apply(image, radius);  // radius is a positive number

Vignette image

// intensity and vignetteWidth are floats between 0.0 and 1.0
PImage processedImage = Vignette.apply(image, intensity, vignetteWidth); 

Quantization

PImage processedImage = Quantization.apply(image, shades);  // shades is a positive number between 1 and 255

PaletteMapping

PImage processedImage = PaletteMapping.apply(image, color1, color2, color3);  // Add any number of colors from dark to light

Difference

// 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);

Blur

Gaussian blur image

PImage processedImage = Gaussian.apply(image, 7, 0.84089642);   // kernel size and sigma 

Pixelize image

// 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);  

Tilt-Shift-Effect

PImage processedImage = TiltShift.apply(image, blurIntensity, horizontal, position, sharpWideness);   

Edge detection

Canny's algorithm

PImage processedImage = CannyEdgeDetector.apply(image);

Sobels algorithm

PImage processedImage = SobelEdgeDetector.apply(image);
// for colored sobel (for each color channel)
PImage processedImage = SobelEdgeDetector.apply(image, false);

Optimisation

Brightness

PImage processedImage = Brightness.apply(image, value); 
// value isa positive number for brighting up or a negative for darken down

Contrast

// intensity is between -1.0 and 1.0
PImage processedImage = Contrast.apply(image, intensity); 

Saturation

// 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); 

Changing highlights

// intensity between -1.0 and 1.0
PImage processedImage = Lights.apply(image, intensity); 

Changing shadows

// intensity between -1.0 and 1.0
PImage processedImage = Shadows.apply(image, intensity); 

AutoBalance image

PImage processedImage = AutoBalance.apply(image);

Bloom image

PImage processedImage = Bloom.apply(image, intensity);  // intensity between 0 and 255

Sharpen image

PImage processedImage = Sharpen.apply(image, sharpIntensity);  // sharpIntensity between 0.0 and 10.0

Color shift image

// 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);

Looks

Lookup table image

LUT style = LUT.loadLut(LUT.STYLE.CONTRAST);
PImage processedImage = LUT.apply(image, style); 

RetroConsole effect (Gameboy)

PImage processedImage = RetroConsole.applyGameboy(image, pixelSize); 

Glitch image

PImage processedImage = Glitch.apply(image, intensity, scanlineheight);

Matte effect

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

Sabattier effect

// 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);

Strokes image

random angles	fixed angle

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

Dithering

// 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);  

Halftone image

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

Toning image

// 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);

Split toning image

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

Sine-Wave image

PImage processedImage = SineWave.apply(image, rowHeight, weight, backgroundColor, wavesColor);

Knitting image

// 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); 

ASCII image

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); 

Miscellaneous

Stacked images

// 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);

Blending two images

// intensity is a float between 0.0 and 1.0
PImage processedImage = Blend.apply(image1, image2, intensity);

Special thanks

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.