数字图像处理 || c++对图像进行对数变换，幂律变换，比特面分层以及均衡化处理

对数变换：

CImg<int> SrcImg;
SrcImg.load_tiff("E:/Desktop/picture_process/Lenna/3/Fig0305(a)(DFT_no_log).tif");
SrcImg.display();
cimg_forXY(SrcImg, x, y) {
	SrcImg(x, y) = int(log(double(SrcImg(x, y)) + 1));
}
SrcImg.display();

运行效果：

幂律变换

CImg<int> SrcImg;
SrcImg.load_tiff("E:/Desktop/picture_process/Lenna/3/Fig0308(a)(fractured_spine).tif");
SrcImg.display();
double t[3] = { 0.6,0.4,0.3 };
for (int i = 0; i < 3; i++) {
	CImg<int> img = SrcImg;
	cimg_forXY(img, x, y) {
		img(x, y) = int(pow(double((img(x, y))), t[i]));
	}
	img.display();
}

运行结果：

比特面分层

CImg<int> img;
	img.load_tiff("E:/Desktop/picture_process/Lenna/3/Fig0314(a)(100-dollars).tif");
	img.display("原图");
	int w = img.height();
	int h = img.width();
	CImg<int> p1(h,w,1,1), p2(h, w, 1, 1), p3(h, w, 1, 1), p4(h, w, 1, 1), p5(h, w, 1, 1), p6(h, w, 1, 1), p7(h, w, 1, 1), p8(h, w, 1, 1);
	cimg_forXY(img, x, y) {
		int num = img(x, y);
		int *bit = binary(num);
		p1(x, y) = fx(bit[0]); p2(x, y) = fx(bit[1]); p3(x, y) = fx(bit[2]); p4(x, y) = fx(bit[3]);
		p5(x, y) = fx(bit[4]); p6(x, y) = fx(bit[5]); p7(x, y) = fx(bit[6]); p8(x, y) = fx(bit[7]);
	}
	p8.display("第八层比特图");
	p7.display("第七层比特图");
	p6.display("第六层比特图");
	p5.display("第五层比特图");
	p4.display("第四层比特图");
	p3.display("第三层比特图");
	p2.display("第二层比特图");
	p1.display("第一层比特图");
}
//用于对图片进行黑白的赋值
int fx(int n) {
	if (n == 1)
		return 255;
	else
		return 0;
}
//用于进行二进制转化的函数
int* binary(int num) {
	int *bit;
	bit = new int[8];
	for (int i = 0; i < 8; i++) {
		bit[i] = 0;
	}
	int i = 0;
	while (num) {
		bit[i] = num % 2;
		num /= 2;
		i++;
	}
	return bit;
}

运行结果：



在这里插入图片描述

均衡化处理

• CImg有专门显示密度分布直方图的histogram函数

	CImg<int> hist = img.histogram(256, 0, 255); //histogram的第一个参数是共有256个灰度级，第二个参数是灰度的最小值，第三个是灰度最大值
	hist.display_graph();

	CImg<int> img;
	img.load_tiff("E:/Desktop/picture_process/Lenna/3/Fig0316(4)(bottom_left).tif");
	CImg<int> pic = img;
	img.display("处理前图片");
	int size = img.size();
	CImg<int> hist = img.histogram(256, 0, 255); //histogram的第一个参数是共有256个灰度级，第二个参数是灰度的最小值，第三个是灰度最大值
	hist.display_graph("处理前直方图");
	double sum = 0.0;
	map<int, int> index;
	for (int i = 0; i < 256; i++) {
		sum += (double) hist(i)/size;
		int Sum = (int)(sum * 255);
		index.insert(pair<int, int>(i, Sum));
	}
	//map<int, int>::iterator iter = index.begin();
	//map<int, int>::iterator end = index.end();
	/*for (; iter != end; iter++) {
		cout << iter->first<<":"<< iter->second << endl;
	}*/
	cimg_forXY(pic, x, y) {
		pic(x, y) = index[pic(x, y)];
		//cout << pic(x, y) << " ";
	}
	pic.display("处理后图片");
	CImg<int> hist1 = pic.histogram(256, 0, 255);
	hist1.display_graph("处理后直方图");

运行结果：