/* * libpipi Proper image processing implementation library * Copyright (c) 2004-2008 Sam Hocevar * All Rights Reserved * * $Id$ * * This library is free software. It comes without any warranty, to * the extent permitted by applicable law. You can redistribute it * and/or modify it under the terms of the Do What The Fuck You Want * To Public License, Version 2, as published by Sam Hocevar. See * http://sam.zoy.org/wtfpl/COPYING for more details. */ /* * median.c: median filter functions */ #include "config.h" #include "common.h" #include #include #include #include #include "pipi.h" #include "pipi_internals.h" pipi_image_t *pipi_median(pipi_image_t *src, int radius) { return pipi_median_ext(src, radius, radius); } /* FIXME: this is in desperate want of optimisation. Here is what could * be done to improve the performance: * - prefetch the neighbourhood; most neighbours are the same as the * previous pixels. * - use a better sort algorithm; bubble sort is ridiculous * - even better, use state-of-the art median selection, ie. O(3n), for * most common combinations (9, 25, 49, 81). */ pipi_image_t *pipi_median_ext(pipi_image_t *src, int rx, int ry) { pipi_image_t *dst; pipi_pixels_t *srcp, *dstp; float *srcdata, *dstdata; double *list; int x, y, w, h, i, j, k, size, gray; w = src->w; h = src->h; size = (2 * rx + 1) * (2 * ry + 1); gray = (src->last_modified == PIPI_PIXELS_Y_F); srcp = gray ? pipi_getpixels(src, PIPI_PIXELS_Y_F) : pipi_getpixels(src, PIPI_PIXELS_RGBA_F); srcdata = (float *)srcp->pixels; dst = pipi_new(w, h); dstp = gray ? pipi_getpixels(dst, PIPI_PIXELS_Y_F) : pipi_getpixels(dst, PIPI_PIXELS_RGBA_F); dstdata = (float *)dstp->pixels; list = malloc(size * (gray ? 1 : 4) * sizeof(double)); for(y = 0; y < h; y++) { for(x = 0; x < w; x++) { double tmp; double *parser = list; /* Make a list of neighbours */ for(j = -ry; j <= ry; j++) { int y2 = y + j; if(y2 < 0) y2 = h - 1 - ((-y2 - 1) % h); else if(y2 > 0) y2 = y2 % h; for(i = -rx; i <= rx; i++) { int x2 = x + i; if(x2 < 0) x2 = w - 1 - ((-x2 - 1) % w); else if(x2 > 0) x2 = x2 % w; if(gray) { *parser++ = srcdata[y2 * w + x2]; } else { *parser++ = srcdata[4 * (y2 * w + x2)]; *parser++ = srcdata[4 * (y2 * w + x2) + 1]; *parser++ = srcdata[4 * (y2 * w + x2) + 2]; *parser++ = srcdata[4 * (y2 * w + x2) + 3]; } } } /* Sort the list */ for(i = 0; i < size; i++) { for(j = 0; j < i; j++) { if(gray) { if(list[i] < list[j]) { tmp = list[i]; list[i] = list[j]; list[j] = tmp; } } else { for(k = 0; k < 4; k++) { if(list[4 * i + k] < list[4 * j + k]) { tmp = list[4 * i + k]; list[4 * i + k] = list[4 * j + k]; list[4 * j + k] = tmp; } } } } } /* Store the median value */ if(gray) { dstdata[y * w + x] = list[size / 2]; } else { dstdata[4 * (y * w + x)] = list[size / 2 * 4]; dstdata[4 * (y * w + x) + 1] = list[size / 2 * 4 + 1]; dstdata[4 * (y * w + x) + 2] = list[size / 2 * 4 + 2]; dstdata[4 * (y * w + x) + 3] = list[size / 2 * 4 + 3]; } } } return dst; }