Superpixel-based Structural Similarity Metric for Image Fusion Quality Evaluation
Superpixel-based Structural Similarity Metric for Image Fusion Quality Evaluation
复制标题
用于图像融合质量评估的基于超像素的结构相似性度量
DOI：
10.1007/s11220-021-00339-1
复制
发表时间：
2021-03-19
影响因子：
2.2
通讯作者：
Pang, Lihui
中科院分区：
文献类型：
--
作者：
Wang, Eryan;Yang, Bin;Pang, Lihui
图像融合是指将同一场景的多幅图像融合成一幅高质量的融合图像。融合图像的通用质量评价是图像融合领域亟待解决的问题之一。通常，从融合图像的矩形块中提取的局部特征用于实现客观评价。然而，图像块的固定形状既不适合图像的自然属性，也不适合人类视觉系统的感知特性。针对这一问题，提出了一种基于超像素的结构相似性度量方法用于图像融合质量评价。从自适应超像素中提取的图像特征用于计算对应超像素之间的结构相似性。然后对所有的局部结构相似性指标按其重要性进行加权平均，得到最终的评价得分。采用几种经典的图像融合质量评价指标进行对比实验分析。一系列实验结果表明，该质量评价指标的稳定性约为10 - 6个数量级，其准确性和性能均优于最新的评价指标。同时，该评价指标得到的评价结果更接近于人眼视觉评价结果。
Image fusion refers to integrate multiple images of the same scene into a high-quality fused image. Universal quality evaluation for fused image is one of the urgent problems in the field of image fusion. Typically, local features extracted from rectangular blocks of the fused images are used to achieve objective evaluation. However, the fixed shape of image block is neither suitable for the natural attributes of an image, nor for the perceptual characteristics of human visual system. To deal with the problem, a superpixel-based structural similarity metric for image fusion quality evaluation is proposed in this paper. The image features extracted from adaptive superpixels are used to calculate the structural similarity between the corresponding superpixels. Then all local structural similarity indicators are weighted and averaged according to their significance to obtain the final evaluation score. Several classical image fusion quality evaluation metrics are used for comparative experimental analysis. A series of experimental results show that the stability of the proposed quality evaluation index is about 10−6orders of magnitude, whose accuracy and performance are more advantageous than the latest evaluation index. Meanwhile, the evaluation results obtained by the proposed metric is closer to the human visual evaluation results.