python图片归一化 opencv 图像归一化

什么是归一化

归一化是指在处理数据的过程中，把数据范围相差较大的数据进行标准化处理，让所有的数据都处于同一个数量级中,在opencv中具体实现有4种方式

步骤1：在pycharm中查看帮助

    输入指令  import cv2 as cv

                     help(cv.normalize)

步骤2：在这里可以看到有4种的归一化方式

方式1：NORM_L1 

          

.       // Norm to probability (total count)
    .       // sum(numbers) = 20.0
    .       // 2.0      0.1     (2.0/20.0)
    .       // 8.0      0.4     (8.0/20.0)
    .       // 10.0     0.5     (10.0/20.0)
    .       normalize(positiveData, normalizedData_l1, 1.0, 0.0, NORM_L1);

方式2：NORM_L2

公式:

// Norm to unit vector: ||positiveData|| = 1.0
    .       // 2.0      0.15    0.15=2/sqrt(2*2+8*8+10*10)
    .       // 8.0      0.62    0.62=8/sqrt(2*2+8*8+10*10)
    .       // 10.0     0.77    0.77=10/sqrt(2*2+8*8+10*10)
    .       normalize(positiveData, normalizedData_l2, 1.0, 0.0, NORM_L2);

方式3：NORM_INF

公式:

// Norm to max element
    .       // 2.0      0.2     (2.0/10.0)
    .       // 8.0      0.8     (8.0/10.0)
    .       // 10.0     1.0     (10.0/10.0)
    .       normalize(positiveData, normalizedData_inf, 1.0, 0.0, NORM_INF);

方式4：NORM_MINMAX

公式

// Norm to range [0.0;1.0]
    .       // 2.0      0.0     (shift to left border)
    .       // 8.0      0.75    (6.0/8.0)
    .       // 10.0     1.0     (shift to right border)
    .       normalize(positiveData, normalizedData_minmax, 1.0, 0.0, NORM_MINMAX);

步骤3：在python中实现四种方式

main.py代码

from numpy import *
from cv2 import *
import OpencvFunc as fc
from matplotlib import pyplot as plt

if __name__ == '__main__':
    titles = ['Orginal', 'NORM_MINMAX','NORM_L1','NORM_L2','NORM_INF']

    Orginalimg=fc.OpenImage("F:/OpencvTest/fail.jpg")

    #NORM_MINMAX
    NORM_MINMAXimg = zeros(Orginalimg.shape, float32)
    NORM_MINMAXimg=fc.normalize(Orginalimg,NORM_MINMAXimg,NORM_MINMAX)
    print(NORM_MINMAXimg)
    # NORM_L1
    NORM_L1img = zeros(Orginalimg.shape, float32)
    NORM_L1img=fc.normalize(Orginalimg,NORM_L1img,NORM_L1)
    print(NORM_L1img)
    # NORM_L2
    NORM_L2img = zeros(Orginalimg.shape, float32)
    NORM_L2img=fc.normalize(Orginalimg,NORM_L2img,NORM_L2)
    print(NORM_L2img)
    # NORM_INF
    NORM_INFimg = zeros(Orginalimg.shape, float32)
    NORM_INFimg=fc.normalize(Orginalimg,NORM_INFimg,NORM_INF)
    print(NORM_L2img)

    images = [Orginalimg, NORM_MINMAXimg, NORM_L1img, NORM_L2img, NORM_INFimg]

    for i in range(len(images)):
        plt.subplot(3, 3, i + 1)
        plt.imshow(images[i], 'gray')
        plt.title(titles[i])
        plt.xticks([]), plt.yticks([])
    plt.show()
    k=waitKey(0)

OpencvFunc.py代码

from numpy import *
import  cv2 as cv

def OpenImage(file):
    im = cv.imread(file)  # 在工程目录下放一张图片
    if im is None:
        print("image as null")
    im = cv.cvtColor(im, cv.COLOR_RGB2GRAY)
    return im
def normalize(src,dst,NormalType):
    if NormalType=="NORM_L1":
        NormalType = "NORM_L1"
    elif NormalType=="NORM_L2":
        NormalType = "NORM_L2"
    elif NormalType == "NORM_INF":
        NormalType = "NORM_INF"
    elif NormalType == "NORM_MINMAX":
        NormalType = "NORM_MINMAX"
    src = float32(src)
   # print(src)
    # NORM_MINMAX
    dst = zeros(src.shape, float32)
    #print(dst)
    cv.normalize(src,dst,1.0,0.0,NormalType)
    return dst

图形效果显示