• 理论
• 代码
• 8. Vollath函数

理论

Vollath函数定义如下：其中：为整幅图像的平均灰度值，M和N分别为图像宽和高。https://blog.csdn.net/Real_Myth/article/details/50827940

代码

def Vollath(img):
    '''
    :param img:narray 二维灰度图像
    :return: float 图像约清晰越大
    '''
    shape = np.shape(img)
    u = np.mean(img)
    out = -shape[0]*shape[1]*(u**2)
    for x in range(0, shape[0]-1):
        for y in range(0, shape[1]):
            out+=int(img[x,y])*int(img[x+1,y])
    return out

https://blog.csdn.net/Greepex/article/details/90183018

def _Vollath(self,imgName):
    """
                   灰度方差乘积
                   :param imgName:
                   :return:
                   """
    # step 1 图像的预处理
    img2gray, reImg = self.preImgOps(imgName)
    f = self._imageToMatrix(img2gray)
    source=0
    x,y=f.shape
    for i in range(x-1):
        for j in range(y):
            source+=f[i,j]*f[i+1,j]
    source=source-x*y*np.mean(f)
    # strp3: 绘制图片并保存  不应该写在这里  抽象出来   这是共有的部分
    newImg = self._drawImgFonts(reImg, str(source))
    newDir = self.strDir + "/_Vollath_/"
    if not os.path.exists(newDir):
        os.makedirs(newDir)
    newPath = newDir + imgName
    cv2.imwrite(newPath, newImg)  # 保存图片
    cv2.imshow(imgName, newImg)
    cv2.waitKey(0)
    return source

https://github.com/Leezhen2014/python—/blob/master/BlurDetection.py

8. Vollath函数

Vollath函数定义如下：其中： u为整幅图像的平均灰度值，M和N分别为图像宽和高。代码:

def Vollath(img):
        # 图像的预处理
        reImg = cv2.resize(img, (800, 900), interpolation=cv2.INTER_CUBIC)  
        img2gray = cv2.cvtColor(reImg, cv2.COLOR_BGR2GRAY)  #
        f = self._imageToMatrix(img2gray)
        D = 0
        x,y=f.shape
        for i in range(x-1):
            for j in range(y):
                D += f[i,j]*f[i+1,j]
        D = D - x * y * np.mean(f)
        return D

https://gist.github.com/JuneoXIE/d595028586eec752f4352444fc062c44