Mat ImageAHE(Mat img, int block) { Mat AHE_GO = img.clone(); int width = img.cols; int height = img.rows; int width_block = width / block; //每个小格子的长和宽 int height_block = height / block; //存储各个直方图 int tmp2[16 * 16][256] = { 0 };//10要和block保持一致 float C2[16 * 16][256] = { 0.0 }; //分块 int total = width_block * height_block;//分割的总的块儿数 for (int i = 0; i < block; i++) { for (int j = 0; j < block; j++) { int start_x = i * width_block; int end_x = start_x + width_block; int start_y = j * height_block; int end_y = start_y + height_block; int num = i + block * j; //遍历小块,计算直方图 for (int ii = start_x; ii < end_x; ii++) { for (int jj = start_y; jj < end_y; jj++) { int index = img.at<uchar>(jj, ii); tmp2[num][index]++; } } //计算累积分布直方图 for (int k = 0; k < 256; k++) { if (k == 0) C2[num][k] = 1.0f * tmp2[num][k] / total; else C2[num][k] = C2[num][k - 1] + 1.0f * tmp2[num][k] / total; } } } //将统计结果写入 for (int i = 0; i < block; i++) { for (int j = 0; j < block; j++) { int start_x = i * width_block; int end_x = start_x + width_block; int start_y = j * height_block; int end_y = start_y + height_block; int num = i + block * j; //遍历小块,计算直方图 for (int ii = start_x; ii < end_x; ii++) { for (int jj = start_y; jj < end_y; jj++) { int index = img.at<uchar>(jj, ii); //结果直接写入AHE_GO中去 AHE_GO.at<uchar>(jj, ii) = C2[num][index] * 255; } } } } return AHE_GO; } Mat ImageEqaualize(Mat img) { int width = img.cols; int height = img.rows; Mat HT_GO = img.clone(); int tmp[256] = { 0 }; float C[256] = { 0.0 }; int total = width * height; for (int i = 0; i < img.rows; i++) { for (int j = 0; j < img.cols; j++) { int index = img.at<uchar>(i, j); tmp[index] ++; } } //计算累积函数 for (int i = 0; i < 256; i++) { if (i == 0) C[i] = 1.0f * tmp[i] / total; else C[i] = C[i - 1] + 1.0f * tmp[i] / total; } //这里的累积函数分配的方法非常直观高效 for (int i = 0; i < img.rows; i++) { for (int j = 0; j < img.cols; j++) { int index = img.at<uchar>(i, j); HT_GO.at<uchar>(i, j) = C[index] * 255; } } return HT_GO; } Mat ImageClHe(Mat img, int block) { int width = img.cols/ block; int height = img.rows/ block; Mat CLHE_GO = img.clone(); int tmp[256] = { 0 }; float C[256] = { 0.0 }; int total = width * height; for (int i = 0; i < img.rows; i++) { for (int j = 0; j < img.cols; j++) { int index = img.at<uchar>(i, j); tmp[index] ++; } } /////////////////////////限制对比度计算部分,注意这个地方average的计算不一定科学 int average = width * height / 255 /64; int LIMIT = 4 * average; int steal = 0; for (int k = 0; k < 256; k++) { if (tmp[k] > LIMIT) { steal += tmp[k] - LIMIT; tmp[k] = LIMIT; } } int bonus = steal / 256; //hand out the steals averagely for (int k = 0; k < 256; k++) { tmp[k] += bonus; } /////////////////////////////////////////// //计算累积函数 for (int i = 0; i < 256; i++) { if (i == 0) C[i] = 1.0f * tmp[i] / total; else C[i] = C[i - 1] + 1.0f * tmp[i] / total; } //这里的累积函数分配的方法非常直观高效 for (int i = 0; i < img.rows; i++) { for (int j = 0; j < img.cols; j++) { int index = img.at<uchar>(i, j); CLHE_GO.at<uchar>(i, j) = C[index] * 255; } } return CLHE_GO; } Mat ImageClHeNoInter(Mat img, int block) { Mat CLAHE_GO = img.clone(); int width = img.cols; int height = img.rows; int width_block = width / block; //每个小格子的长和宽 int height_block = height / block; //存储各个直方图 int tmp2[8 * 8][256] = { 0 }; float C2[8 * 8][256] = { 0.0 }; //分块 int total = width_block * height_block; for (int i = 0; i < block; i++) { for (int j = 0; j < block; j++) { int start_x = i * width_block; int end_x = start_x + width_block; int start_y = j * height_block; int end_y = start_y + height_block; int num = i + block * j; //遍历小块,计算直方图 for (int ii = start_x; ii < end_x; ii++) { for (int jj = start_y; jj < end_y; jj++) { int index = img.at<uchar>(jj, ii); tmp2[num][index]++; } } //裁剪和增加操作，也就是clahe中的cl部分 //这里的参数 对应《Gem》上面 fCliplimit = 4 , uiNrBins = 255 int average = width_block * height_block / 255; int LIMIT = 4 * average; int steal = 0; for (int k = 0; k < 256; k++) { if (tmp2[num][k] > LIMIT) { steal += tmp2[num][k] - LIMIT; tmp2[num][k] = LIMIT; } } int bonus = steal / 256; //hand out the steals averagely for (int k = 0; k < 256; k++) { tmp2[num][k] += bonus; } //计算累积分布直方图 for (int k = 0; k < 256; k++) { if (k == 0) C2[num][k] = 1.0f * tmp2[num][k] / total; else C2[num][k] = C2[num][k - 1] + 1.0f * tmp2[num][k] / total; } } } //计算变换后的像素值 //将统计结果写入 for (int i = 0; i < block; i++) { for (int j = 0; j < block; j++) { int start_x = i * width_block; int end_x = start_x + width_block; int start_y = j * height_block; int end_y = start_y + height_block; int num = i + block * j; //遍历小块,计算直方图 for (int ii = start_x; ii < end_x; ii++) { for (int jj = start_y; jj < end_y; jj++) { int index = img.at<uchar>(jj, ii); //结果直接写入AHE_GO中去 CLAHE_GO.at<uchar>(jj, ii) = C2[num][index] * 255; } } } } return CLAHE_GO; } Mat ImageClahe(Mat img, int block) { Mat CLAHE_GO = img.clone(); //int block = _step;//pblock int width = img.cols; int height = img.rows; int width_block = width / block; //每个小格子的长和宽 int height_block = height / block; //存储各个直方图 int tmp2[8 * 8][256] = { 0 }; float C2[8 * 8][256] = { 0.0 }; //分块 int total = width_block * height_block; for (int i = 0; i < block; i++) { for (int j = 0; j < block; j++) { int start_x = i * width_block; int end_x = start_x + width_block; int start_y = j * height_block; int end_y = start_y + height_block; int num = i + block * j; //遍历小块,计算直方图 for (int ii = start_x; ii < end_x; ii++) { for (int jj = start_y; jj < end_y; jj++) { int index = img.at<uchar>(jj, ii); tmp2[num][index]++; } } //裁剪和增加操作，也就是clahe中的cl部分 //这里的参数 对应《Gem》上面 fCliplimit = 4 , uiNrBins = 255 int average = width_block * height_block / 255; //关于参数如何选择，需要进行讨论。不同的结果进行讨论 //关于全局的时候，这里的这个cl如何算，需要进行讨论 int LIMIT = 40 * average; int steal = 0; for (int k = 0; k < 256; k++) { if (tmp2[num][k] > LIMIT) { steal += tmp2[num][k] - LIMIT; tmp2[num][k] = LIMIT; } } int bonus = steal / 256; //hand out the steals averagely for (int k = 0; k < 256; k++) { tmp2[num][k] += bonus; } //计算累积分布直方图 for (int k = 0; k < 256; k++) { if (k == 0) C2[num][k] = 1.0f * tmp2[num][k] / total; else C2[num][k] = C2[num][k - 1] + 1.0f * tmp2[num][k] / total; } } } //计算变换后的像素值 //根据像素点的位置，选择不同的计算方法 for (int i = 0; i < width; i++) { for (int j = 0; j < height; j++) { //four coners if (i <= width_block / 2 && j <= height_block / 2) { int num = 0; CLAHE_GO.at<uchar>(j, i) = (int)(C2[num][CLAHE_GO.at<uchar>(j, i)] * 255); } else if (i <= width_block / 2 && j >= ((block - 1)*height_block + height_block / 2)) { int num = block * (block - 1); CLAHE_GO.at<uchar>(j, i) = (int)(C2[num][CLAHE_GO.at<uchar>(j, i)] * 255); } else if (i >= ((block - 1)*width_block + width_block / 2) && j <= height_block / 2) { int num = block - 1; CLAHE_GO.at<uchar>(j, i) = (int)(C2[num][CLAHE_GO.at<uchar>(j, i)] * 255); } else if (i >= ((block - 1)*width_block + width_block / 2) && j >= ((block - 1)*height_block + height_block / 2)) { int num = block * block - 1; CLAHE_GO.at<uchar>(j, i) = (int)(C2[num][CLAHE_GO.at<uchar>(j, i)] * 255); } //four edges except coners else if (i <= width_block / 2) { //线性插值 int num_i = 0; int num_j = (j - height_block / 2) / height_block; int num1 = num_j * block + num_i; int num2 = num1 + block; float p = (j - (num_j*height_block + height_block / 2)) / (1.0f*height_block); float q = 1 - p; CLAHE_GO.at<uchar>(j, i) = (int)((q*C2[num1][CLAHE_GO.at<uchar>(j, i)] + p * C2[num2][CLAHE_GO.at<uchar>(j, i)]) * 255); } else if (i >= ((block - 1)*width_block + width_block / 2)) { //线性插值 int num_i = block - 1; int num_j = (j - height_block / 2) / height_block; int num1 = num_j * block + num_i; int num2 = num1 + block; float p = (j - (num_j*height_block + height_block / 2)) / (1.0f*height_block); float q = 1 - p; CLAHE_GO.at<uchar>(j, i) = (int)((q*C2[num1][CLAHE_GO.at<uchar>(j, i)] + p * C2[num2][CLAHE_GO.at<uchar>(j, i)]) * 255); } else if (j <= height_block / 2) { //线性插值 int num_i = (i - width_block / 2) / width_block; int num_j = 0; int num1 = num_j * block + num_i; int num2 = num1 + 1; float p = (i - (num_i*width_block + width_block / 2)) / (1.0f*width_block); float q = 1 - p; CLAHE_GO.at<uchar>(j, i) = (int)((q*C2[num1][CLAHE_GO.at<uchar>(j, i)] + p * C2[num2][CLAHE_GO.at<uchar>(j, i)]) * 255); } else if (j >= ((block - 1)*height_block + height_block / 2)) { //线性插值 int num_i = (i - width_block / 2) / width_block; int num_j = block - 1; int num1 = num_j * block + num_i; int num2 = num1 + 1; float p = (i - (num_i*width_block + width_block / 2)) / (1.0f*width_block); float q = 1 - p; CLAHE_GO.at<uchar>(j, i) = (int)((q*C2[num1][CLAHE_GO.at<uchar>(j, i)] + p * C2[num2][CLAHE_GO.at<uchar>(j, i)]) * 255); } //双线性插值 else { int num_i = (i - width_block / 2) / width_block; int num_j = (j - height_block / 2) / height_block; int num1 = num_j * block + num_i; int num2 = num1 + 1; int num3 = num1 + block; int num4 = num2 + block; float u = (i - (num_i*width_block + width_block / 2)) / (1.0f*width_block); float v = (j - (num_j*height_block + height_block / 2)) / (1.0f*height_block); CLAHE_GO.at<uchar>(j, i) = (int)((u*v*C2[num4][CLAHE_GO.at<uchar>(j, i)] + (1 - v)*(1 - u)*C2[num1][CLAHE_GO.at<uchar>(j, i)] + u * (1 - v)*C2[num2][CLAHE_GO.at<uchar>(j, i)] + v * (1 - u)*C2[num3][CLAHE_GO.at<uchar>(j, i)]) * 255); } //最后这步，类似高斯平滑 CLAHE_GO.at<uchar>(j, i) = CLAHE_GO.at<uchar>(j, i) + (CLAHE_GO.at<uchar>(j, i) << 8) + (CLAHE_GO.at<uchar>(j, i) << 16); } } return CLAHE_GO; }