贵州两学一做网站,开发软件多少钱,家在深圳家在布吉,wordpress添加超链接对比度增强#xff0c;即将图片的灰度范围拉宽#xff0c;如图片灰度分布范围在[50,150]之间#xff0c;将其范围拉升到[0,256]之间。这里介绍下 线性变换#xff0c;直方图正规化#xff0c;伽马变换#xff0c;全局直方图均衡化#xff0c;限制对比度自适应直方图均衡…对比度增强即将图片的灰度范围拉宽如图片灰度分布范围在[50,150]之间将其范围拉升到[0,256]之间。这里介绍下 线性变换直方图正规化伽马变换全局直方图均衡化限制对比度自适应直方图均衡化等算法。
线性变换
通过函数yaxb对灰度值进行处理例如对于过暗的图片其灰度分布在[0,100], 选择a2,b10能将灰度范围拉伸到[10, 210]。可以通过np或者opencv的convertScaleAbs()函数来实现 。
#coding:utf-8import cv2 as cv
import matplotlib.pyplot as plt
import numpy as np
from cv2 import convertScaleAbsimg cv.imread(rC:\Users\mzd\Desktop\opencv\images.jpg)
print(img)
img_bright cv.convertScaleAbs(img,alpha1.5,beta0)
print(img_bright)cv.imshow(img,img)
cv.imshow(img_bright,img_bright)
cv.waitKey(0)
cv.destroyAllWindows()convertScaleAbs()直方图正规化
#coding:utf-8import cv2 as cv
import matplotlib.pyplot as plt
import numpy as npimg cv.imread(rC:\Users\mzd\Desktop\opencv\images.jpg)
img_normcv.normalize(img,dstNone,alpha350,beta10,norm_typecv.NORM_MINMAX)
cv.imshow(img,img)
cv.imshow(img_norm,img_norm)
cv.waitKey(0)
cv.destroyAllWindows()cv.normalize()全局直方图均衡化
#coding:utf-8import cv2 as cv
import matplotlib.pyplot as plt
import numpy as np
import mathimg cv.imread(rC:\Users\Administrator\Desktop\dark.jpg,0)
img_equalize cv.equalizeHist(img)
cv.imshow(img,img)
cv.imshow(img_equalize,img_equalize)
cv.waitKey(0)
cv.destroyAllWindows()opencv equalizeHist()