Python cv2 图像自适应灰度直方图均衡化处理方法

wlpython 2018-12-07

__author__ = 'Administrator'

import numpy as np
import cv2
 
mri_img = np.load('mri_img.npy')
 
# normalization
mri_max = np.amax(mri_img)
mri_min = np.amin(mri_img)
mri_img = ((mri_img-mri_min)/(mri_max-mri_min))*255
mri_img = mri_img.astype('uint8')
 
r, c, h = mri_img.shape
for k in range(h):
 temp = mri_img[:,:,k]
 clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
 img = clahe.apply(temp)
 cv2.imshow('mri', np.concatenate([temp,img], 1))
 cv2.waitKey(0)

均衡化前、后对比效果

Python cv2 图像自适应灰度直方图均衡化处理方法

Python cv2 图像自适应灰度直方图均衡化处理方法

Python cv2 图像自适应灰度直方图均衡化处理方法

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