python客观评价图像拼接融合质量代码

以下是一个基于OpenCV库的图像拼接和融合质量评价的Python代码示例：

import cv2
import numpy as np

def stitch_images(images):
    stitcher = cv2.createStitcher() if cv2.__version__.startswith('3') else cv2.Stitcher_create()
    status, stitched = stitcher.stitch(images)
    if status == 0:
        return stitched
    else:
        return None

def evaluate_fusion_quality(image1, image2, fused_image):
    # calculate the absolute difference between the fused image and the input images
    diff1 = cv2.absdiff(fused_image, image1)
    diff2 = cv2.absdiff(fused_image, image2)
    # calculate the mean squared error between the fused image and the input images
    mse1 = np.mean(diff1 ** 2)
    mse2 = np.mean(diff2 ** 2)
    # calculate the peak signal-to-noise ratio (PSNR)
    psnr1 = cv2.PSNR(fused_image, image1)
    psnr2 = cv2.PSNR(fused_image, image2)
    # calculate the structural similarity index (SSIM)
    ssim1 = cv2.SSIM(fused_image, image1)
    ssim2 = cv2.SSIM(fused_image, image2)
    # return the evaluation metrics for both input images
    return {
        'mse1': mse1,
        'mse2': mse2,
        'psnr1': psnr1,
        'psnr2': psnr2,
        'ssim1': ssim1,
        'ssim2': ssim2
    }

# example usage
image1 = cv2.imread('image1.jpg')
image2 = cv2.imread('image2.jpg')
stitched_image = stitch_images([image1, image2])
if stitched_image is not None:
    fused_image = cv2.addWeighted(image1, 0.5, image2, 0.5, 0)
    metrics = evaluate_fusion_quality(image1, image2, fused_image)
    print(metrics)
else:
    print('Error: unable to stitch images')

这个代码使用OpenCV库提供的图像拼接器创建一个拼接图像，然后计算两个输入图像与融合图像之间的差异，并计算评价指标，例如均方误差（MSE），峰值信噪比（PSNR）和结构相似性指数（SSIM）。