Update speed_filter2d_in_gray_image.cpp

Author: BBuf

Algorithm optimization/README.md

@@ -0,0 +1,4 @@
+# Algorithm optimization 优化一些常见的OpenCV算法
+
+- speed_filter2d_in_gray_image.cpp 使用OpenBLAS和OpenMP优化对灰度图的卷积算法(filter2D)
+- 

Algorithm optimization/speed_filter2d_in_gray_image.cpp

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+#include <iostream>
+#include <stdio.h>
+#include <cblas.h>
+#include <opencv2/opencv.hpp>
+
+using namespace std;
+using namespace cv;
+
+//使用OpenMp和OpenBlas加速filter2D（灰度图）,且卷积核的长宽相等，这里实现的是长宽均为3的卷积核
+//RGB转化为灰度图
+Mat speed_rgb2gray(Mat src) {
+	Mat dst(src.rows, src.cols, CV_8UC1);
+#pragma omp parallel for num_threads(4)
+	for (int i = 0; i < src.rows; i++) {
+		for (int j = 0; j < src.cols; j++) {
+			dst.at<uchar>(i, j) = ((src.at<Vec3b>(i, j)[0] << 18) + (src.at<Vec3b>(i, j)[0] << 15) + (src.at<Vec3b>(i, j)[0] << 14) +
+				(src.at<Vec3b>(i, j)[0] << 11) + (src.at<Vec3b>(i, j)[0] << 7) + (src.at<Vec3b>(i, j)[0] << 7) + (src.at<Vec3b>(i, j)[0] << 5) +
+				(src.at<Vec3b>(i, j)[0] << 4) + (src.at<Vec3b>(i, j)[0] << 2) +
+				(src.at<Vec3b>(i, j)[1] << 19) + (src.at<Vec3b>(i, j)[1] << 16) + (src.at<Vec3b>(i, j)[1] << 14) + (src.at<Vec3b>(i, j)[1] << 13) +
+				(src.at<Vec3b>(i, j)[1] << 10) + (src.at<Vec3b>(i, j)[1] << 8) + (src.at<Vec3b>(i, j)[1] << 4) + (src.at<Vec3b>(i, j)[1] << 3) + (src.at<Vec3b>(i, j)[1] << 1) +
+				(src.at<Vec3b>(i, j)[2] << 16) + (src.at<Vec3b>(i, j)[2] << 15) + (src.at<Vec3b>(i, j)[2] << 14) + (src.at<Vec3b>(i, j)[2] << 12) +
+				(src.at<Vec3b>(i, j)[2] << 9) + (src.at<Vec3b>(i, j)[2] << 7) + (src.at<Vec3b>(i, j)[2] << 6) + (src.at<Vec3b>(i, j)[2] << 5) + (src.at<Vec3b>(i, j)[2] << 4) + (src.at<Vec3b>(i, j)[2] << 1) >> 20);
+		}
+	}
+	return dst;
+}
+
+//A增加Pad的运算
+void get_Pad(int pad_Height, int pad_Width, int row, int col, float *A_pad, float *A) {
+	int pad_x = pad_Height - row >> 1;
+	int pad_y = pad_Width - col >> 1;
+	printf("pad_x: %d pad_y: %d\n", pad_x, pad_y);
+	for (int i = 0; i < pad_Height; i++) {
+		for (int j = 0; j < pad_Width; j++) {
+			int index = i * pad_Height + j;
+			if (i <= pad_x || i + pad_x > pad_Height) {
+				A_pad[index] = 0;
+			}
+			else {
+				if (j <= pad_y || j + pad_y > pad_Width) {
+					A_pad[index] = 0;
+				}
+				else {
+					A_pad[index] = A[(i - pad_x) * row + j - pad_y];
+				}
+			}
+		}
+	}
+}
+
+
+
+int main() {
+	Mat src = cv::imread("F:\\1.jpg");
+	src = speed_rgb2gray(src);
+	int row = src.rows;
+	int col = src.cols;
+	// 将原始的
+	float *A = new float[row * col];
+	for (int i = 0; i < row * col; i++) {
+		int x = i / row;
+		int y = i % row;
+		A[i] = src.at<float>(x, y);
+	}
+	const int KernelHeight = 3;
+	const int KernelWidth = 3;
+	float B[KernelHeight * KernelWidth] = { 1, 1, 1, 1, 1, 1, 1, 1, 1 };
+	//卷积核参数初始化为
+	const int pad = (KernelHeight - 1) / 2; //需要pad的长度
+	const int stride = 1; //卷积核滑动的步长
+	//计算卷积输出矩阵的长宽
+	const int OutHeight = (row - KernelHeight + 2 * pad) / stride + 1;
+	const int OutWidth = (col - KernelWidth + 2 * pad) / stride + 1;
+	//计算pad_A
+	const int pad_Height = row + 2 * pad;
+	const int pad_Width = col + 2 * pad;
+	float *A_pad = new float[pad_Height * pad_Width];
+	get_Pad(pad_Height, pad_Width, row, col, A_pad, A);
+
+}

README.md

@@ -10,6 +10,8 @@
 
 ## 5. Color Space Conversion 实现和优化各种色彩空间转换算法
 
+## 6. Algorithm optimization 优化一些常见的OpenCV算法
+
 - Retinex MSRCR.cpp 带色彩恢复的多尺度视网膜增强算法。 算法原理请看：http://www.cnblogs.com/Imageshop/archive/2013/04/17/3026881.html
 - ImageDataIncrease.cpp 常见的图片数据扩充。包括一些PS算法 具体为旋转，添加高斯，椒盐噪声，增加老照片效果，增加和降低图像饱和度，对原图缩放，亮度增强，对比度增强，磨皮美白，偏色矫正，同态滤波，过曝，灰度化，轮换通道，图像错切，运动模糊，钝化蒙版，PS滤镜算法之球面化 (凸出和凹陷效果)
 - HDR.cpp C++复现《Adaptive Local Tone Mapping Based on Retinex for High Dynamic Range Images》， 实现低照度彩色图像恢复。算法原理请看：https://blog.csdn.net/just_sort/article/details/84030723