【学习记录】去除彩色图像的的黑色/阴影区域

工作中，遇到的问题，原来论坛中是C++版本，自己写成的python版本，仅供参考。

原文链接

How to remove black/shadows regions of colored Image via OpenCV - OpenCV Q&A Forum

cvtColor(src, gray, CV_BGR2GRAY);
// get full available range
double minGray,maxGray;
cv::minMaxLoc(gray, &minGray, &maxGray);
//suppose current range is 30...220

bool useRelative = true;
if(useRelative)
{
    // Relative clipping dark range to black
    double clipPercent = 10; 
    minGray = cvRound(minGray * (1 + clipPercent/100.0) );
    //all below minGray+10% will become black
}
else
{
    //absolute clipping. Use a fixed lower bound for dark regions
    double minGrayWanted = 50; 
    minGray = minGrayWanted;
    //all below 50 will become black
}

// current range
float inputRange = maxGray - minGray;

alpha = 255.0 / inputRange; // alpha expands current range. MaxGray will be 255
beta = -minGray * alpha;    // beta shifts current range so that minGray will go to 0

src.convertTo(dst, -1, alpha, beta);

python版本

def shape_detection_v3(img):
    '''识别到颜色之后，进行形状检测
    c++>python
    '''
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    minGray ,maxGray,_,_ = cv2.minMaxLoc(gray,mask=None)
    useRelative = True
    if useRelative:
        # 相对裁剪暗范围到黑色
        clipPercent = 10
        minGray = np.round(minGray*(1+clipPercent/100.0))

    else:
        minGrayWanted = 100
        minGray = minGrayWanted
    inputRange =  maxGray-minGray
    alpha = 255.0/inputRange
    beta = -minGray*alpha

    '''
    src.convertTo(dst,-1,alpha,beta)
            @param参数列表
            (
            OutputArray,m
    		int 	rtype,
            double 	alpha = 1 ,	可选比例因子
            double 	beta = 0  , 添加到缩放值的可选增量。
            )
    '''
    res = cv2.convertScaleAbs(img,alpha,beta)
    cv2.imshow('img',img)
    cv2.imshow('res',res)
    cv2.waitKey(0)

    if cv2.waitKey(10)==27:
        exit(0)

个人心得

想消除图片的阴影的话，在处理灰度图之前，可以尝试一下增加图片对比度。

'''转入灰度图之前增强对比度'''
 Alpha = 65.6
 Gamma=-8191.5
 cal = cv2.addWeighted(img, Alpha,img, 0, Gamma)
 gray = cv2.cvtColor(cal, cv2.COLOR_BGR2GRAY)

获取亮度和对比度数值的代码也随手分享一下

'''BrightnessContrast,controller查看对比度'''
def BrightnessContrast(brightness=0):
    # getTrackbarPos returns the current
    # position of the specified trackbar.
    brightness = cv2.getTrackbarPos('Brightness',
                                    'GEEK')

    contrast = cv2.getTrackbarPos('Contrast',
                                  'GEEK')

    effect = controller(img, brightness,contrast)

    # The function imshow displays an image
    # in the specified window
    cv2.imshow('test', effect)
    cv2.imshow('test', effect)
    if cv2.waitKey(10)==27:
        exit(0)
        # cv2.destoryAllWindows()



def controller(img,brightness=255,contrast=127):
    # 亮度
    brightness = int((brightness - 0) * (255 - (-255)) / (510 - 0) + (-255))
    #对比度
    contrast = int((contrast - 0) * (127 - (-127)) / (254 - 0) + (-127))

    if brightness!=0:
        if brightness>0:

            shadow = brightness
            max=255
        else:
            shadow = 0
            max = 255+brightness
        al_pha = (max-shadow)/255
        ga_mma = shadow

        cal = cv2.addWeighted(img,al_pha,img,0,ga_mma)
    else:
        cal = img
    if contrast != 0:
        Alpha = float(131 * (contrast + 127)) / (127 * (131 - contrast))
        Gamma = 127 * (1 - Alpha)

        # The function addWeighted calculates
        # the weighted sum of two arrays
        # print(Alpha,Gamma)
        # 65.5 - 8191.5
        cal = cv2.addWeighted(cal, Alpha,
                              cal, 0, Gamma)

        # putText renders the specified text string in the image.
    cv2.putText(cal, 'B:{},C:{}'.format(brightness,
                                        contrast), (10, 30),
                cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)

    return cal
if __name__ =='__main__':
    img = cv2.imread('color.png')
    iimg = img.copy()
     cv2.namedWindow('GEEK')
     cv2.imshow('GEEK',img)
     cv2.createTrackbar('Brightness',
                        'GEEK', 255, 2 * 255,
                        BrightnessContrast)

     # Contrast range -127 to 127
     cv2.createTrackbar('Contrast', 'GEEK',
                        127, 2 * 127,
                        BrightnessContrast)

     BrightnessContrast(0)
cv2.waitKey(0)