二、图像运算、融合、类型转换

柔光的暖阳◎ 2023-06-13 09:47 81阅读 0赞

**目录**

一、图像加法

二、图像融合

三、图像类型转换

--------------------

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3MyOTQ4NzgzMDQ_size_16_color_FFFFFF_t_70][]

# 一、图像加法 #

图像的大小及数值类型必须一致

**1、numpy的图像加法**

若某个像素相加之和大于255，则相加后的值除以 255取余

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3MyOTQ4NzgzMDQ_size_16_color_FFFFFF_t_70 1][]

**2、opencv的图像加法**

若某个像素相加之和大于255，则取 255

# encoding: utf-8
    
    import cv2
    import matplotlib.pyplot as plt
    import math
    import copy
    import numpy as np
    # 每行三个图像，输入一个图像列表
    def show_img(img):
        plt.figure()
        plt.imshow(img)
        plt.show()
    
    path = r"E:\PythonProjects\python_study\opencv\lena.jpg"
    img1 = cv2.imread(path)
    gray = cv2.cvtColor(img1,cv2.COLOR_RGB2GRAY)
    
    print("=============CV2图像加法==============")
    add_cv1 = cv2.add(img1,img2)
    show_img(add_cv1)

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3MyOTQ4NzgzMDQ_size_16_color_FFFFFF_t_70 2][]

# 二、图像融合 #

addWeighted（）函数是将两张相同大小，相同类型的图片融合的函数。他可以实现图片的特效。

dst = cv.addWeighted(src1, alpha, src2, beta,gamma)

*  src1：插入的第一个图片；
 *  src2：插入的第二个图片；
 *  alpha：double类型，加权系数，是src1图片的融合占比 ；
 *  beta：double类型，加权系数，是src2图片的融合占比；
 *  gamma：亮度调节值；

该函数的计算公式为:

dst(I)=saturate(src1(I)∗alpha+src2(I)∗beta+gamma)

# encoding: utf-8
    
    import cv2
    import matplotlib.pyplot as plt
    import math
    import copy
    import numpy as np
    # 每行三个图像，输入一个图像列表
    def show_img(img):
        plt.figure()
        plt.imshow(img)
        plt.show()
    
    path1 = r"E:\PythonProjects\python_study\opencv\lena.jpg"
    path2 = r"E:\PythonProjects\python_study\opencv\jingwu.jpg"
    img1 = cv2.imread(path1)
    img2 = cv2.imread(path2)
    img2 = cv2.resize(img2,(512,512),interpolation=cv2.INTER_CUBIC)
    gray = cv2.cvtColor(img1,cv2.COLOR_RGB2GRAY)
    print("=================================")
    print(img1.shape)
    print(img2.reshape)
    img3 = cv2.addWeighted(img1,0.7,img2,0.2,0)
    show_img(img3)

# 三、图像类型转换 #

OpenCV转换成PIL.Image格式

image = Image.fromarray(cv2.cvtColor(img,cv2.COLOR_BGR2RGB))

Image转换成OpenCV格式

img = cv2.cvtColor(numpy.asarray(image),cv2.COLOR_RGB2BGR)

# encoding: utf-8
    
    import cv2
    import matplotlib.pyplot as plt
    import math
    import copy
    import numpy as np
    # 每行三个图像，输入一个图像列表
    def show_img(img):
        plt.figure()
        plt.imshow(img)
        plt.show()
    
    path1 = r"E:\PythonProjects\python_study\opencv\lena.jpg"
    img1 = cv2.imread(path1)
    # bgr 2 gray
    gray = cv2.cvtColor(img1,cv2.COLOR_BGR2GRAY)
    # bgr 2 rgb
    rgb = cv2.cvtColor(img1,cv2.COLOR_BGR2RGB)
    # gray 2 bgr
    bgr1 = cv2.cvtColor(gray,cv2.COLOR_GRAY2BGR)
    print(gray.shape)# (512, 512)
    print(bgr1.shape)# (512, 512, 3)

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3MyOTQ4NzgzMDQ_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/2019111601025744.jpg?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3MyOTQ4NzgzMDQ=,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3MyOTQ4NzgzMDQ_size_16_color_FFFFFF_t_70 1]: https://img-blog.csdnimg.cn/20191116011047327.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3MyOTQ4NzgzMDQ=,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3MyOTQ4NzgzMDQ_size_16_color_FFFFFF_t_70 2]: https://img-blog.csdnimg.cn/2019111601110441.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3MyOTQ4NzgzMDQ=,size_16,color_FFFFFF,t_70