對(duì)每個(gè)像素點(diǎn)的三通道值進(jìn)行同步放大，同時(shí)保持通道值在0-255之間

將圖像中的像素限制在最小值和最大值之間，超過(guò)此區(qū)間的值賦值為最小值或最大值

圖片亮度增強(qiáng)

import cv2 import numpy as np import matplotlib.pyplot as pltimg = cv2.imread('1.png', 1) height, width = img.shape[:2]dst = np.zeros((height, width, 3), np.uint8) for i in range(0, height):for j in range(0, width):(b, g, r) = img[i, j]bb = int(b) + 50gg = int(g) + 50rr = int(r) + 50if bb > 255:bb = 255if gg > 255:gg = 255if rr > 255:rr = 255dst[i, j] = (bb, gg, rr)img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) dst = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB) plt.figure(figsize=(14, 6), dpi=100) # 設(shè)置繪圖區(qū)域的大小和像素 plt.subplot(121) plt.imshow(img) plt.subplot(122) plt.imshow(dst) plt.show()

運(yùn)行結(jié)果：

import cv2 import numpy as np import matplotlib.pyplot as pltimg = cv2.imread('1.png', 1) height, width = img.shape[:2]dst = np.zeros((height, width, 3), np.uint8) for i in range(0, height):for j in range(0, width):(b, g, r) = img[i, j]bb = int(b * 1.3) + 10gg = int(g * 1.2) + 15if bb > 255:bb = 255if gg > 255:gg = 255dst[i, j] = (bb, gg, r)img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) dst = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB) plt.figure(figsize=(14, 6), dpi=100) # 設(shè)置繪圖區(qū)域的大小和像素 plt.subplot(121) plt.imshow(img) plt.subplot(122) plt.imshow(dst) plt.show()

運(yùn)行結(jié)果：

圖片亮度減弱

import cv2 import numpy as np import matplotlib.pyplot as pltimg = cv2.imread('1.png', 1) height, width = img.shape[:2]dst = np.zeros((height, width, 3), np.uint8) for i in range(0, height):for j in range(0, width):(b, g, r) = img[i, j]bb = int(b) - 50gg = int(g) - 50rr = int(r) - 50if bb < 0:bb = 0if gg < 0:gg = 0if rr < 0:rr = 0dst[i, j] = (bb, gg, rr)img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) dst = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB) plt.figure(figsize=(14, 6), dpi=100) # 設(shè)置繪圖區(qū)域的大小和像素 plt.subplot(121) plt.imshow(img) plt.subplot(122) plt.imshow(dst) plt.show()

運(yùn)行結(jié)果：

總結(jié)

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