63 lines
2.7 KiB
Python
63 lines
2.7 KiB
Python
import numpy as np
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from PIL import Image
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from skimage import exposure
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from matplotlib import colors
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def match_image_hsv(source_path, reference_path, output_path):
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# 1. 读取图片并归一化到 0-1 (matplotlib 的 hsv 转换需要 0-1)
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src_rgb = np.array(Image.open(source_path)) / 255.0
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ref_rgb = np.array(Image.open(reference_path)) / 255.0
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# 2. 将图片从 RGB 转换为 HSV
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src_hsv = colors.rgb_to_hsv(src_rgb)
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ref_hsv = colors.rgb_to_hsv(ref_rgb)
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# 3. 分离 HSV 通道
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# src_h: 色调, src_s: 饱和度, src_v: 亮度
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s_h, s_s, s_v = src_hsv[:,:,0], src_hsv[:,:,1], src_hsv[:,:,2]
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r_h, r_s, r_v = ref_hsv[:,:,0], ref_hsv[:,:,1], ref_hsv[:,:,2]
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# 4. 对 V (亮度) 和 S (饱和度) 通道进行直方图匹配
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# 我们使用参考图的 V 和 S 分布来调整源图
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matched_h = exposure.match_histograms(s_h, r_h)
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matched_v = exposure.match_histograms(s_v, r_v)
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matched_s = exposure.match_histograms(s_s, r_s)
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# 5. 合并通道
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# 使用原始的 H (色调)，加上匹配后的 S 和 V
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# V1 不调整H版本
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matched_hsv = np.stack([s_h, matched_s, matched_v], axis=2)
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# V2 调整H版本
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# matched_hsv = np.stack([matched_h, matched_s, matched_v], axis=2)
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# 6. 转换回 RGB 并保存
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# 转换回 RGB 后需要 clip 到 0-1 范围，防止数值溢出
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matched_rgb = np.clip(colors.hsv_to_rgb(matched_hsv), 0, 1)
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# 将 0-1 转换回 0-255 的整数并保存
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result_image = Image.fromarray((matched_rgb * 255).astype(np.uint8))
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result_image.save(output_path)
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print(f"HSV 处理完成，图片已保存至: {output_path}")
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def match_image_appearance(source_path, reference_path, output_path):
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# 1. 读取图片
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# source: 需要调整的图片 (第一张, 偏暗)
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# reference: 目标风格图片 (第二张, 正常)
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src = np.array(Image.open(source_path))
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ref = np.array(Image.open(reference_path))
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# 2. 进行直方图匹配
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# channel_axis=-1 表示对 RGB 每个通道分别进行匹配
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matched = exposure.match_histograms(src, ref, channel_axis=-1)
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# 3. 保存结果
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result_image = Image.fromarray(matched.astype(np.uint8))
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result_image.save(output_path)
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print(f"处理完成，图片已保存至: {output_path}")
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# 使用示例
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source_file = "./去雾图像-北航合作/2025-07-02_084220_VID002.mp4_20251027_001308.661.png"
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reference_file = "./去雾图像-北航合作-Result_Baidu/2025-07-02_084220_VID002.mp4_20251027_001308.661.png"
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# V1
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# match_image_appearance(source_file, reference_file, "adjusted_image_rgb.png")
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# V2
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match_image_hsv(source_file, reference_file, "adjusted_image_hsv.png") |