Fast mean fuzzy algorithm and mean Fuzzy Algorithm

Fast mean fuzzy algorithm and mean Fuzzy Algorithm

I saw a fast mean fuzzy algorithm on the internet some time ago, with good performance.

Source blog:

Http://www.lellansin.com/super-fast-blur-%E6%A8%A1%E7%B3%8A%E7% AE %97%E6%B3%95.html

The blogger corrected the bug and optimized its performance.

The algorithm is used on the VM to blur a x image, which takes-milliseconds and is very fast.

The Code is as follows:

/** Super Fast Blur v1.1+* Original author: Mario Klingemann (C++ version)* Original address: http://incubator.quasimondo.com/processing/superfastblur.pde* C version updated by Lellansin (http://www.lellansin.com)* C version bugfix and performance optimization by tntmonks (http://tntmonks.cnblogs.com)*/void superFastBlur(unsigned char *pix, unsigned int w, unsigned int h, unsigned int comp, int radius){unsigned int div;unsigned int wm, hm, wh;unsigned int *vMIN, *vMAX;unsigned char *r, *g, *b, *dv;unsigned int rsum, gsum, bsum;unsigned int p, p1, p2, yi, yw;int x, y, i, yp;if (radius < 1)return;wm = w - 1;hm = h - 1;wh = w * h;div = radius + radius + 1;vMIN = (unsigned int *)malloc(sizeof(unsigned int) * max(w, h));vMAX = (unsigned int *)malloc(sizeof(unsigned int) * max(w, h));r = (unsigned char *)malloc(sizeof(unsigned char) * wh);g = (unsigned char *)malloc(sizeof(unsigned char) * wh);b = (unsigned char *)malloc(sizeof(unsigned char) * wh);dv = (unsigned char *)malloc(sizeof(unsigned char) * 256 * div);for (i = 0; i < 256 * div; i++)dv[i] = (i / div);yw = yi = 0;for (y = 0; y < h; y++){rsum = gsum = bsum = 0;for (i = -radius; i <= radius; i++){p = (yi + min(wm, max(i, 0))) * comp;bsum += pix[p];gsum += pix[p + 1];rsum += pix[p + 2];}for (x = 0; x < w; x++){r[yi] = dv[rsum];g[yi] = dv[gsum];b[yi] = dv[bsum];if (y == 0){vMIN[x] = min(x + radius + 1, wm);vMAX[x] = max(x - radius, 0);}p1 = (yw + vMIN[x]) * comp;p2 = (yw + vMAX[x]) * comp;bsum += pix[p1] - pix[p2];gsum += pix[p1 + 1] - pix[p2 + 1];rsum += pix[p1 + 2] - pix[p2 + 2];yi++;}yw += w;}for (x = 0; x < w; x++){rsum = gsum = bsum = 0;yp = -radius * w;for (i = -radius; i <= radius; i++){yi = max(0, yp) + x;rsum += r[yi];gsum += g[yi];bsum += b[yi];yp += w;}yi = x;for (y = 0; y < h; y++){ pix[yi * comp] = (dv[bsum]);pix[yi * comp + 1] = (dv[gsum]);pix[yi * comp + 2] = (dv[rsum]);if (x == 0){vMIN[y] = min(y + radius + 1, hm) * w;vMAX[y] = max(y - radius, 0) * w;}p1 = x + vMIN[y];p2 = x + vMAX[y];rsum += r[p1] - r[p2];gsum += g[p1] - g[p2];bsum += b[p1] - b[p2];yi += w;}} free(r); free(g); free(b); free(vMIN); free(vMAX); free(dv);}

This algorithm can be simply modified for image enhancement.

The algorithm can be further optimized, and this task will be handed over to the audience.