opencv 灰度直方图和彩色直方图像素分布绘制

女爷i 2021-11-09 05:02 386阅读 0赞

1，灰度直方图的绘制：

# 1 0-255 2 概率 
    # 本质：统计每个像素灰度 出现的概率 0-255 p
    import cv2
    import numpy as np
    import matplotlib.pyplot as plt
    img = cv2.imread('image0.jpg',1)
    imgInfo = img.shape
    height = imgInfo[0]
    width = imgInfo[1]
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    count = np.zeros(256,np.float)
    for i in range(0,height):
        for j in range(0,width):
            pixel = gray[i,j]
            index = int(pixel)
            count[index] = count[index]+1
    for i in range(0,255):
        count[i] = count[i]/(height*width)
    x = np.linspace(0,255,256)
    y = count
    plt.bar(x,y,0.9,alpha=1,color='b')
    plt.show()
    cv2.waitKey(0)

结果如下：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMDA4MzI1_size_16_color_FFFFFF_t_70][]

2，彩色图的r,g,b直方图代码实现：

# 本质：统计每个像素灰度 出现的概率 0-255 p
    import cv2
    import numpy as np
    import matplotlib.pyplot as plt
    img = cv2.imread('image0.jpg',1)
    imgInfo = img.shape
    height = imgInfo[0]
    width = imgInfo[1]
    
    count_b = np.zeros(256,np.float)
    count_g = np.zeros(256,np.float)
    count_r = np.zeros(256,np.float)
    for i in range(0,height):
        for j in range(0,width):
            (b,g,r) = img[i,j]
            index_b = int(b)
            index_g = int(g)
            index_r = int(r)
            count_b[index_b] = count_b[index_b]+1
            count_g[index_g] = count_g[index_g]+1
            count_r[index_r] = count_r[index_r]+1
    for i in range(0,256):
        count_b[i] = count_b[i]/(height*width)
        count_g[i] = count_g[i]/(height*width)
        count_r[i] = count_r[i]/(height*width)
    x = np.linspace(0,255,256)
    y1 = count_b
    plt.figure()
    plt.bar(x,y1,0.9,alpha=1,color='b')
    y2 = count_g
    plt.figure()
    plt.bar(x,y2,0.9,alpha=1,color='g')
    y3 = count_r
    plt.figure()
    plt.bar(x,y3,0.9,alpha=1,color='r')
    plt.show()
    cv2.waitKey(0)

结果如下：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMDA4MzI1_size_16_color_FFFFFF_t_70 1][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMDA4MzI1_size_16_color_FFFFFF_t_70 2][]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMDA4MzI1_size_16_color_FFFFFF_t_70]: /images/20211109/c7d90767763e4950a2cc54e9486d3663.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMDA4MzI1_size_16_color_FFFFFF_t_70 1]: /images/20211109/2b64bf1e78b84860a411d95121f05d7e.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMDA4MzI1_size_16_color_FFFFFF_t_70 2]: /images/20211109/3ae7fbffe73a4ff39142eae5afe4920c.png