opencv图像增强、图像模糊方法对比

朱雀 2023-06-20 06:14 176阅读 0赞

# 图像增强： #

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zODI5MzQ1Mw_size_16_color_FFFFFF_t_70][]

Mat image = imread("../lic_image/lic_image/20140209220432703.png", 1);
        if (image.empty())
        {
            std::cout << "打开图片失败,请检查" << std::endl;
            return -1;
        }
        imwrite("../lic_image/output/origin.png",image);
        imshow("原图像", image);
        Mat imageEnhance;
    
    
      //    cv::blur(image,image,cv::Size(5,5));
       //cv::Laplacian(image,imageEnhance,CV_8U,1,1,128);
        cv::Laplacian(image,imageEnhance,CV_8U,7,0.01,128);
    
        imwrite("../lic_image/output/lapulasi.png",imageEnhance);
        imshow("拉普拉斯算子图像增强效果", imageEnhance);
    
    
    
        image=imageEnhance;
    
        Mat imageRGB[3];
        split(image, imageRGB);
        for (int i = 0; i < 3; i++)
        {
            equalizeHist(imageRGB[i], imageRGB[i]);
        }
        Mat equalizeHistDist;
        merge(imageRGB, 3, equalizeHistDist);
    
        imwrite("../lic_image/output/equalizeHistDist.png",equalizeHistDist);
        imshow("直方图均衡化图像增强效果", equalizeHistDist);
    
    
    
    
    
        Mat imageLog(image.size(), CV_32FC3);
        for (int i = 0; i < image.rows; i++)
        {
            for (int j = 0; j < image.cols; j++)
            {
                imageLog.at<Vec3f>(i, j)[0] = log(1 + image.at<Vec3b>(i, j)[0]);
                imageLog.at<Vec3f>(i, j)[1] = log(1 + image.at<Vec3b>(i, j)[1]);
                imageLog.at<Vec3f>(i, j)[2] = log(1 + image.at<Vec3b>(i, j)[2]);
            }
        }
        //归一化到0~255
        normalize(imageLog, imageLog, 0, 255, NORM_MINMAX);
        //转换成8bit图像显示
        convertScaleAbs(imageLog, imageLog);
        imwrite("../lic_image/output/imageLog.png",imageLog);
        imshow("imageLog图像增强效果", imageLog);
    
    
        Mat imageGamma(image.size(), CV_32FC3);
        for (int i = 0; i < image.rows; i++)
        {
            for (int j = 0; j < image.cols; j++)
            {
                imageGamma.at<Vec3f>(i, j)[0] = (image.at<Vec3b>(i, j)[0])*(image.at<Vec3b>(i, j)[0])*(image.at<Vec3b>(i, j)[0]);
                imageGamma.at<Vec3f>(i, j)[1] = (image.at<Vec3b>(i, j)[1])*(image.at<Vec3b>(i, j)[1])*(image.at<Vec3b>(i, j)[1]);
                imageGamma.at<Vec3f>(i, j)[2] = (image.at<Vec3b>(i, j)[2])*(image.at<Vec3b>(i, j)[2])*(image.at<Vec3b>(i, j)[2]);
            }
        }
        //归一化到0~255
        normalize(imageGamma, imageGamma, 0, 255, NORM_MINMAX);
        //转换成8bit图像显示
        convertScaleAbs(imageGamma, imageGamma);
        imwrite("../lic_image/output/imageGamma.png",imageGamma);
        imshow("imageGamma图像增强效果", imageGamma);
    
    
       Mat new_image = Mat::zeros( image.size(), image.type() );
       double alpha = 0.6; /*< Simple contrast control */
       int beta = 20;       /*< Simple brightness control */
       for( int y = 0; y < image.rows; y++ ) {
               for( int x = 0; x < image.cols; x++ ) {
                   for( int c = 0; c < image.channels(); c++ ) {
                       new_image.at<Vec3b>(y,x)[c] =
                         saturate_cast<uchar>( alpha*image.at<Vec3b>(y,x)[c] + beta );
                   }
               }
           }
    
       imwrite("../lic_image/output/imageab.png",new_image);
       imshow("imageab图像增强效果", new_image);

图像模糊：image\_smooth.py

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zODI5MzQ1Mw_size_16_color_FFFFFF_t_70 1][]

import numpy as np
    import cv2 as cv
    from matplotlib import pyplot as plt
    
    img = cv.imread("./lic_image/lic_image/lic_enhance/20140209215818359.png")
    path="4"
    kernel = np.ones((5,5),np.float32)/25
    filter2D = cv.filter2D(img,-1,kernel)
    blur = cv.blur(img,(5,5))
    gaussianblur = cv.GaussianBlur(img,(5,5),0)
    medianblur = cv.medianBlur(img,5)
    bilateralblur = cv.bilateralFilter(img,9,75,75)
    
    plt.subplot(231),plt.imshow(img),plt.title('Original')
    plt.xticks([]), plt.yticks([])
    
    cv.imwrite("./lic_image/output/"+path+"/Original.png",img)
    
    
    plt.subplot(232),plt.imshow(filter2D),plt.title('filter2D')
    plt.xticks([]), plt.yticks([])
    cv.imwrite("./lic_image/output/"+path+"/filter2D.png",filter2D)
    
    plt.subplot(233),plt.imshow(blur),plt.title('blur')
    plt.xticks([]), plt.yticks([])
    cv.imwrite("./lic_image/output/"+path+"/blur.png",blur)
    
    plt.subplot(234),plt.imshow(gaussianblur),plt.title('gaussianblur')
    plt.xticks([]), plt.yticks([])
    cv.imwrite("./lic_image/output/"+path+"/gaussianblur.png",gaussianblur)
    
    plt.subplot(235),plt.imshow(medianblur),plt.title('medianblur')
    plt.xticks([]), plt.yticks([])
    cv.imwrite("./lic_image/output/"+path+"/medianblur.png",medianblur)
    
    plt.subplot(236),plt.imshow(bilateralblur),plt.title('bilateralblur')
    plt.xticks([]), plt.yticks([])
    cv.imwrite("./lic_image/output/"+path+"/bilateralblur.png",bilateralblur)
    plt.show()

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zODI5MzQ1Mw_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/20191208132255402.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zODI5MzQ1Mw==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zODI5MzQ1Mw_size_16_color_FFFFFF_t_70 1]: https://img-blog.csdnimg.cn/20191208133716253.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zODI5MzQ1Mw==,size_16,color_FFFFFF,t_70