数字图像处理 || CImg实现平滑空间滤波

1.平滑线性滤波器:

自己实现了用于空间平滑滤波的函数:

CImg<int> Smooth_filter(CImg<int> img, int num) {
	CImg<int> m(num, num);
	cimg_forXY(m, x, y) {
		m(x, y) = 1;
	}
	int w = img.width(), h = img.height();
	int k = (num - 1) / 2;
	CImg<int> pic(w, h, 1, 1);
	pic = img;
	pic.resize(w + 2 * k, h + 2 * k, 1, 1);
	CImg<int> pic1 = pic;
	if (num % 2 == 0) {
		cout << "不合法" << endl;
	}
	else {
		CImg<int> temp(w,h,1,1);
		cimg_forXY(pic, x, y) {
			if (x >= k && y >= k && x <= w + k - 1 && y <= h + k - 1) {
				CImg<int> t(num, num);
				for (int i = 0; i < num; i++) {
					for (int j = 0; j < num; j++) {
						t(i, j) = pic1(x-k+i, y-k+j);
					}
				}
				double sum = 0.0;
				cimg_forXY(t, i1, j1) {
					cimg_forXY(m, i2, j2) {
						if (i1 + i2 - k == 1 && j1 + j2 - k == 1) {
							sum += (double)t(i1, j1)*m(i2, j2);
						}
					}
				}
				pic(x, y) = sum / num / num;
			}
		}
		
	}
	return pic;
}

使用3*3的矩阵进行平滑滤波后的效果:

在这里插入图片描述
在这里插入图片描述

2.中值滤波器:

CImg<int> median_filter(CImg<int> img, int num) {
	int w = img.width(), h = img.height();
	int k = (num - 1) / 2;
	CImg<int> pic(w, h, 1, 1);
	pic = img;
	pic.resize(w + 2 * k, h + 2 * k, 1, 1);
	CImg<int> pic1 = pic;
	if (num % 2 == 0) {
		cout << "不合法" << endl;
	}
	else {
		CImg<int> temp(w, h, 1, 1);
		cimg_forXY(pic, x, y) {
			if (x >= k && y >= k && x <= w + k - 1 && y <= h + k - 1) {
				CImg<int> t(num, num);
				int a = num * num;
				int *filter;
				filter = new int[a];
				for (int i = 0; i < num; i++) {
					for (int j = 0; j < num; j++) {
						t(i, j) = pic1(x - k + i, y - k + j);
						filter[i*num + j] = t(i, j);
					}
				}
				sort(filter,filter+a);
				pic(x, y) = filter[(a + 1) / 2 - 1];
			}
		}

	}
	return pic;
}

使用3*3中值滤波器的滤波效果:
在这里插入图片描述

使用CImg封装的中值滤波器检验一下效果—blur_median
在这里插入图片描述

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转载自blog.csdn.net/perry0528/article/details/82878197