def ImgHist(image,type):

    color = (255,255,255)

    windowName='gray'

    if type==31:

        color=(255,0,0)

        windowName='B'

    elif type==32:

        color=(0,255,0)

        windowName='G'

    elif type==33:

        color=(0,0,255)

        windowName='R'

    #[0]通道

    hist=cv2.calcHist([image],[0],None,[256],[0.0,255.0])

    minV,maxV,minL,maxL=cv2.minMaxLoc(hist)

    print('minV,maxV,minL,maxL',minV,maxV,minL,maxL)

    histImg=np.zeros([256,256,3],np.uint8)

    for i in range(256):

        intenNormal=int(hist[i]*256/maxV)

        print(hist[i],hist[i]*256/maxV)

        cv2.line(histImg,(i,256),(i,256-intenNormal),color)

    cv2.imshow(windowName,histImg)

    return histImg

img=cv2.imread('b.png',1)

channels=cv2.split(img)#RGB--->R  G   B

for i in range(3):

    ImgHist(channels[i],31+i)

cv2.waitKey(0)

img = cv2.imread('b.png',1)

gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)#原图

dst=cv2.equalizeHist(gray)#均衡化

cv2.imshow('dst',dst)

cv2.imshow('gray',gray)

cv2.waitKey(0)

img=cv2.imread('b.png',1)

b,g,r=cv2.split(img)

bH=cv2.equalizeHist(b)

gH=cv2.equalizeHist(g)

rH=cv2.equalizeHist(r)

dst=cv2.merge((bH,gH,rH))

cv2.imshow('dst',dst)

cv2.waitKey(0)

imgyuv=cv2.cvtColor(img,cv2.COLOR_BGR2YCrCb)

channels=cv2.split(imgyuv)

channels[0]=cv2.equalizeHist(channels[0])

channels[1]=cv2.equalizeHist(channels[1])

channels[2]=cv2.equalizeHist(channels[2])

dst=cv2.merge(channels)#融合通道

cv2.imshow('dst',dst)

cv2.waitKey(0)

# 2 双边滤波器

cv2.imshow('src',img)

dst=cv2.bilateralFilter(img,100,200,160)

cv2.imshow('shangbian',dst)

# cv2.waitKey(0)

# 高斯中值滤波

dst=np.zeros(img.shape,np.uint8)

height=img.shape[0]

width=img.shape[1]

for i in range(3,height-3):

    for j in range(3,width-3):

        sum_b=int(0)

        sum_g=int(0)

        sum_r=int(0)

        for m in range(-3,3):

            for n in range(-3,3):

                (b,g,r)=img[i+m,j+n]

                sum_b=sum_b+int(b)

                sum_g=sum_g+int(g)

                sum_r=sum_r+int(r)

        b=np.uint8(sum_b/36)

        g=np.uint8(sum_g/36)

        r=np.uint8(sum_r/36)

        dst[i,j]=(b,g,r)

cv2.imshow('gaosi',dst)

cv2.waitKey(0)