To illustrate this recipe, we will apply a processing function that sharpens an image（銳化圖像的處理函數(shù)）. This time, the processing cannot be accomplished in-place. Users need to provide an output image. The image scanning(掃描)is done using three pointers, one for the current line, one for the line above, and another one for the line below.

　　Since filtering is a common operation in image processing, OpenCV has defined a special function that performs this task: the cv::filter2D function. Note that it is particularly advantageous(特別有利) to use the filter2D function with a large kernel, in this case, a more efficient algorithm.

#include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include <opencv2/imgproc/imgproc.hpp> using namespace cv; void sharpen(const Mat &image, Mat &result) ; void sharpen2D(const Mat &image, Mat &result);int main() {Mat image = imread("test.jpg");resize(image, image, Size(), 0.6, 0.6);Mat result1;Mat result2;namedWindow("YunFung Image");imshow("YunFung Image", image);sharpen(image, result1);namedWindow("Result1");imshow("Result1", result1);sharpen2D(image, result2);namedWindow("Result2");imshow("Result2", result2);waitKey();return 0; }void sharpen(const Mat &image, Mat &result) {result.create(image.size(), image.type()); // allocate if necessaryint nchannels = image.channels();for (int j = 1; j < image.rows - 1; j++) { // for all rows (except first and last)const uchar* previous = image.ptr<const uchar>(j - 1); // previous rowconst uchar* current = image.ptr<const uchar>(j); // current rowconst uchar* next = image.ptr<const uchar>(j + 1); // next row uchar* output = result.ptr<uchar>(j); // output row pointer//saturate_cast<uchar> changing negative values to 0 and values over 255 to 255//sharpened_pixel = 5 * current - left - right - up - down;for (int i = nchannels; i < (image.cols - 1)*nchannels; i++) {*output++ = saturate_cast<uchar>(5 * current[i] - current[i - nchannels]- current[i + nchannels] - previous[i] - next[i]);}}// Set the unprocessed pixels to 0 - left - right - up - downresult.row(0).setTo(Scalar(0));result.row(result.rows - 1).setTo(Scalar(0));result.col(0).setTo(Scalar(0));result.col(result.cols - 1).setTo(Scalar(0)); } void sharpen2D(const Mat &image, Mat &result) {// Construct kernel (all entries initialized to 0)Mat kernel(3, 3, CV_32F, Scalar(0));// assigns kernel valueskernel.at<float>(1, 1) = 5.0;kernel.at<float>(0, 1) = -1.0;kernel.at<float>(2, 1) = -1.0;kernel.at<float>(1, 0) = -1.0;kernel.at<float>(1, 2) = -1.0;//filter the image filter2D(image, result, image.depth(), kernel); }

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轉(zhuǎn)載于:https://www.cnblogs.com/yunfung/p/7560811.html

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