1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79

// drawing-filter.cpp : 素描滤镜
// @mango

#include <iostream>
#include <opencv2/opencv.hpp>
#include<cmath>

int main()
{
	cv::Mat img = cv::imread("fruit.jpg");
	if (img.empty())
	{
		std::cout << "Failed to read the image!" << std::endl;
		return -1;
	}

	//1、去色
	cv::Mat gray(img.size(), CV_8UC3);
	for (size_t i = 0; i < img.rows; i++)
	{
		for (size_t j = 0; j < img.cols; j++)
		{
			int max = std::max(
				std::max(img.at<cv::Vec3b>(i, j)[0], img.at<cv::Vec3b>(i, j)[1]),
				img.at<cv::Vec3b>(i, j)[2]
			);

			int min = std::min(
				std::min(img.at<cv::Vec3b>(i, j)[0], img.at<cv::Vec3b>(i, j)[1]),
				img.at<cv::Vec3b>(i, j)[2]
			);

			for (size_t k = 0; k < 3; k++)
			{
				gray.at<cv::Vec3b>(i, j)[k] = (max + min) / 2;
			}
		}
	}

	//2、复制去色图层，并且反色
	cv::Mat gray_revesal(img.size(), CV_8UC3);
	for (size_t i = 0; i < gray.rows; i++)
	{
		for (size_t j = 0; j < gray.cols; j++)
		{
			for (size_t k = 0; k < 3; k++)
			{
				gray_revesal.at<cv::Vec3b>(i, j)[k] = 255 - gray.at<cv::Vec3b>(i, j)[k];
			}
		}
	}

	//3、对反色图像进行高斯模糊；
	cv::GaussianBlur(gray_revesal, gray_revesal, cv::Size(7, 7), 0);

	//4、模糊后的图像叠加模式选择颜色减淡效果。
	// 减淡公式：C =MIN( A +（A×B）/（255-B）,255)，其中C为混合结果，A为去色后的像素点，B为高斯模糊后的像素点。
	cv::Mat result(gray.size(), CV_8UC3);
	for (size_t i = 0; i < gray.rows; i++)
	{
		for (size_t j = 0; j < gray.cols; j++)
		{
			for (size_t k = 0; k < 3; k++)
			{
				int a = gray.at<cv::Vec3b>(i, j)[k];
				int b = gray_revesal.at<cv::Vec3b>(i, j)[k];
				int c = std::min(a + (a * b) / (255 - b), 255);

				result.at<cv::Vec3b>(i, j)[k] = c;
			}

		}
	}

	cv::imshow("素描效果", result);
	cv::waitKey(0);

	return 0;
}