Python cv2 图像自适应灰度直方图均衡化处理方法

__author__ = 'administrator'

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									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)