如何使用Python对图片进行图像增强

from PIL import Imageimport numpy as npimport matplotlib.pyplot as plt

# 读取图片img = Image.open('example.jpg')# 显示图片plt.imshow(img)plt.axis('off')plt.show()

# 调整图像亮度def adjust_brightness(img, factor):    # 将图像转为numpy数组    img_array = np.array(img)        # 通过调整每个像素点的RGB值来改变亮度    adjusted_array = img_array * factor        # 将改变后的数组转为图像    adjusted_img = Image.fromarray(adjusted_array.astype('uint8'))        return adjusted_img# 设置亮度调整参数brightness_factor = 1.5# 调整亮度并显示结果adjusted_img = adjust_brightness(img, brightness_factor)plt.imshow(adjusted_img)plt.axis('off')plt.show()

# 调整图像对比度def adjust_contrast(img, factor):    # 将图像转为numpy数组    img_array = np.array(img)        # 通过调整每个像素点的亮度差值来改变对比度    adjusted_array = (img_array - img_array.mean()) * factor + img_array.mean()        # 将改变后的数组转为图像    adjusted_img = Image.fromarray(adjusted_array.astype('uint8'))        return adjusted_img# 设置对比度调整参数contrast_factor = 1.5# 调整对比度并显示结果adjusted_img = adjust_contrast(img, contrast_factor)plt.imshow(adjusted_img)plt.axis('off')plt.show()

# 应用图像滤波器def apply_filter(img, filter):    # 将图像转为numpy数组    img_array = np.array(img)        # 应用滤波器    filtered_array = np.convolve(img_array.flatten(), filter.flatten(), mode='same').reshape(img_array.shape)        # 将滤波后的数组转为图像    filtered_img = Image.fromarray(filtered_array.astype('uint8'))        return filtered_img# 设置滤波器filter = np.array([[1, 1, 1],                   [1, -8, 1],                   [1, 1, 1]])# 应用滤波器并显示结果filtered_img = apply_filter(img, filter)plt.imshow(filtered_img)plt.axis('off')plt.show()