Blur

/**
 * Blur.
 *
 * This program analyzes every pixel in an image and blends it with the
 * neighboring pixels to blur the image.
 *
 * This is an example of an "image convolution" using a kernel (small matrix)
 * to analyze and transform a pixel based on the values of its neighbors.
 *
 * Image blur is also called a "low-pass filter". Pixels of low frequency
 * change (similar brightness as neighbors) are left mostly unchanged, while
 * those with high frequency change (sharply different values) are smoothed
 * out.
 *
 * The kernel here is a Box Blur, in which all components are equally valued.
 * Another common blur is "Gaussian Blur", in which pixels nearer the center
 * of the kernel have more weight than those further away.
 */

float v = 1.0 / 9.0;
float kernel[3][3] = {{ v, v, v },
                       { v, v, v },
                       { v, v, v }};

PImage* img;

void setup() {
  size(640, 360);
  img = loadImage("moon.jpg"); // Load the original image
  noLoop();
}

void draw() {
  image(img, 0, 0); // Displays the image from point (0,0)
  img->loadPixels();

  // Create an opaque image of the same size as the original
  PImage* blurImg = createImage(img->width, img->height, RGB);

  // Loop through every pixel in the image
  for (int y = 1; y < img->height - 1; y++) {     // Skip top and bottom edges
    for (int x = 1; x < img->width - 1; x++) {    // Skip left and right edges
      float sumRed = 0;   // Kernel sums for this pixel
      float sumGreen = 0;
      float sumBlue = 0;
      for (int ky = -1; ky <= 1; ky++) {
        for (int kx = -1; kx <= 1; kx++) {
          // Calculate the adjacent pixel for this kernel point
          int pos = (y + ky) * img->width + (x + kx);

          // Process each channel separately, Red first.
          float valRed = red(img->pixels[pos]);
          // Multiply adjacent pixels based on the kernel values
          sumRed += kernel[ky + 1][kx + 1] * valRed;

          // Green
          float valGreen = green(img->pixels[pos]);
          sumGreen += kernel[ky + 1][kx + 1] * valGreen;

          // Blue
          float valBlue = blue(img->pixels[pos]);
          sumBlue += kernel[ky + 1][kx + 1] * valBlue;
        }
      }
      // For this pixel in the new image, set the output value
      // based on the sum from the kernel
      blurImg->pixels[y * blurImg->width + x] = color(sumRed, sumGreen, sumBlue);
    }
  }
  // State that there are changes to blurImg->pixels[]
  blurImg->updatePixels();

  image(blurImg, width / 2, 0); // Draw the new image
}