实验3目录

实验内容

运行效果

项目源码

Sources

DigitalGraphicExp3.cpp

expTransform.cpp 

linearTransform.cpp

logTransform.cpp

Headers

expTransform.h

linearTransform.h

logTransform.h 

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实验内容

1. 读入一副图像，转换为灰度图像，分别使用对数、指数、线性拉伸的灰度变换方法对图像进行变换，比较变换前后的图像；

运行效果

原图：

 

灰度读入：

 

灰度化图像的指数变换：

 

 

 

 

原图的指数变换：

对数图像：

线性拉伸：

项目源码

项目组织格式：

Sources

DigitalGraphicExp3.cpp

// DigitalGraphicExp3.cpp

#include "pch.h"
#include <iostream>
#include <opencv2/opencv.hpp>
#include "expTransform.h"
#include "logTransform.h"
#include "linearTransform.h"

using namespace cv;

int main()
{
	String img_name = "../media/cat.jpg";
	
	// Log
	 logTransform(img_name);
	
	// Exp
	expTransform(img_name);

	// Linear
	linearTransform(img_name);

	return 0;
}

expTransform.cpp 

// expTransform.cpp

#include "expTransform.h"


static void init_lookup_table(uchar* lookup_table) {
	double c = 0.8;
	int r = 2;
	for (int i = 0; i < 256; ++i) {
		lookup_table[i] = int((c * pow(i / 255.0, r)) * 255 + 0.5);
	}
}

void applyExp(Mat& I, const uchar* const table) {
	uchar *p_row = NULL;  //  Start position of the row
	int nRow = I.rows;
	int nCol = I.cols * I.channels();
	if (I.isContinuous()) {
		nCol *= nRow;
		nRow = 1;
	}
	for (int i = 0; i < nRow; ++i) {
		p_row = I.ptr<uchar>(i);

		for (int j = 0; j < nCol; ++j) {
			p_row[j] = table[p_row[j]];
		}
	}
}

void expTransform(String img_dir) {
	uchar lookup_table[256];
	String dir1 = "../media/cat.jpg";
	init_lookup_table(lookup_table);
	if (!img_dir.empty()) {
		dir1 = img_dir;
	}
	Mat src = imread(dir1, IMREAD_GRAYSCALE);
	if (src.empty()) {
		std::cout << "Open Error" << std::endl;
		std::cout << "dir1 = " << dir1 << std::endl;
		waitKey(0);
		return;
	}
	Mat dst = src.clone();
	applyExp(dst, lookup_table);
	imshow("ORIGIN IMG", src);
	imshow("Exp IMG", dst);
	waitKey(0);
}

linearTransform.cpp

// linearTransform.cpp

#include "linearTransform.h"

void linearTransform(String img_dir) {
	String dir1 = "../media/cat.jpg";
	if (!img_dir.empty()) {
		dir1 = img_dir;
	}
	Mat src = imread(dir1, IMREAD_GRAYSCALE);
	if (src.empty()) {
		std::cout << "Open Error" << std::endl;
#ifdef Debug
		std::cout << "dir1 = " << dir1 << std::endl;
		waitKey(0);
#endif
		return;
	}
	Mat dst = src.clone();
	int nRows = dst.rows;
	int nCols = dst.cols;
	if (dst.isContinuous())
	{
		nCols = nCols * nRows;
		nRows = 1;
	}
	uchar *pDataMat;
	int pixMax = 0, pixMin = 255;
	for (int j = 0; j < nRows; j++)
	{
		pDataMat = dst.ptr<uchar>(j);
		for (int i = 0; i < nCols; i++)
		{
			if (pDataMat[i] > pixMax)
				pixMax = pDataMat[i];
			if (pDataMat[i] < pixMin)
				pixMin = pDataMat[i];
		}
	}
	// Linear stretch
	for (int j = 0; j < nRows; j++)
	{
		pDataMat = dst.ptr<uchar>(j);
		for (int i = 0; i < nCols; i++)
		{
			pDataMat[i] = (pDataMat[i] - pixMin) *
				255 / (pixMax - pixMin);
		}
	}
	imshow("Linear Streach", dst);

	waitKey(0);
}

logTransform.cpp

// logTransform.cpp

#include "expTransform.h"
#include <cmath>

void logTransform(String img_dir) {
	String dir1 = "../media/cat.jpg";
	if (img_dir.empty()) {
		dir1 = img_dir;
	}
	Mat srcImage = imread(dir1, IMREAD_GRAYSCALE);
	int c = 2;
	if (srcImage.empty()) {
		std :: cout << "Open Error" << std :: endl;
	}
	Mat resultImage = Mat::zeros(srcImage.size(), srcImage.type());
	add(srcImage, Scalar(1.0), srcImage);
	srcImage.convertTo(srcImage, CV_32F);
	log(srcImage, resultImage);
	resultImage = c * resultImage;
	// normalize
	normalize(resultImage, resultImage, 0, 255, NORM_MINMAX);
	convertScaleAbs(resultImage, resultImage);
	imshow("LOG IMG", resultImage);
}

 

Headers

expTransform.h

// expTransform.h
#pragma once

#include <opencv.hpp>
using namespace cv;

void applyExp(Mat& I, const uchar* const table);
void expTransform(String dir="");

linearTransform.h

// linearTransform.h

#pragma once

#include <opencv.hpp>
using namespace cv;

void linearTransform(String dir = "");

logTransform.h 

// logTransform.h

#pragma once

#include <opencv.hpp>
using namespace cv;

void logTransform(String dir = "");