评价指标测试
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								image_fusion/evaluate_module/evaluation_test.py
									
									
									
									
									
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								image_fusion/evaluate_module/evaluation_test.py
									
									
									
									
									
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from evaluate import *
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# 创建模拟图像数据用于测试
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# img1_gray:原始灰度图像(可见光)
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# img2_gray:变换后的灰度图像(红外模拟)
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# fusion_img:融合图像(可见光 + 红外)
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# ref_img_for_ssim:参考图像(可见光RGB)
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# 创建基础灰度图像(梯度)
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img1_gray = np.tile(np.linspace(50, 200, 256).astype(np.uint8), (256, 1))
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# 模拟配准后的图像:加一点噪声和平移
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img2_gray = np.roll(img1_gray, shift=5, axis=1)  # 平移模拟配准偏差
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noise = np.random.normal(0, 5, img2_gray.shape).astype(np.uint8)
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img2_gray = cv2.add(img2_gray, noise)
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# 创建 RGB 可见光图(重复三个通道)
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ref_img_for_ssim = cv2.merge([img1_gray] * 3)
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# 创建融合图像(取两个灰度图平均后合并入RGB)
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fusion_Y = cv2.addWeighted(img1_gray, 0.5, img2_gray, 0.5, 0)
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fusion_img = cv2.merge([fusion_Y, img1_gray, img2_gray])
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# 运行评价函数
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scores = evaluate_all(img1_gray, img2_gray, fusion_img, ref_img_for_ssim)
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