Python代码实现图像增强（线性变换、对数变换(1)，Python高级开发面试题

效果：

2. 对比度拉伸

代码：

import cv2
import imutils
import numpy as np

image = cv2.imread(‘E:/city.PNG’)

image = cv2.imread(‘E:/city.PNG’)
gray_img = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

在灰度图进行分段线性对比度拉伸

此种方式变换函数把灰度级由原来的线性拉伸到整个范围[0, 255]

r_min, r_max = 255, 0
for i in range(gray_img.shape[0]):
for j in range(gray_img.shape[1]):
if gray_img[i, j] > r_max:
r_max = gray_img[i, j]
if gray_img[i, j] < r_min:
r_min = gray_img[i, j]
r1, s1 = r_min, 0
r2, s2 = r_max, 255

precewise_img = np.zeros((gray_img.shape[0], gray_img.shape[1]), dtype=np.uint8)
k1 = s1 / r1
k3 = (255 - s2) / (255 - r2)
k2 = (s2 - s1) / (r2 - r1)
for i in range(gray_img.shape[0]):
for j in range(gray_img.shape[1]):
if r1 <= gray_img[i, j] <= r2:
precewise_img[i, j] = k2 * (gray_img[i, j] - r1)
elif gray_img[i, j] < r1:
precewise_img[i, j] = k1 * gray_img[i, j]
elif gray_img[i, j] > r2:
precewise_img[i, j] = k3 * (gray_img[i, j] - r2)

cv2.imshow(‘origin image’, imutils.resize(image, 480))
cv2.imshow(‘gray image’, imutils.resize(gray_img, 480))
cv2.imshow(‘precewise image’, imutils.resize(precewise_img, 480))
if cv2.waitKey(0) == 27:
cv2.destroyAllWindows()

效果：

3. 灰度级分层

代码：

import cv2
import imutils
import numpy as np

在某一范围(A, B)突出灰度，其他灰度值保持不变

image = cv2.imread(‘E:/city.PNG’)
gray_img = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

r_left, r_right = 150, 230
r_min, r_max = 0, 255
level_img = np.zeros((gray_img.shape[0], gray_img.shape[1]), dtype=np.uint8)
for