鲸鱼优化算法优化的PCNN医学图像融合

Ritwik Raha, Arpan Sengupta, Supriya Dhabal
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引用次数: 0

摘要

提出了一种基于鲸鱼优化算法(WOA)的改进脉冲耦合神经网络(PCNN)的医学图像融合算法。在该算法中,两幅图像通过WOA进行传递,WOA通过多准则适应度函数计算PCNN特征提取器所需的参数。这样提取的特征然后用于融合图像。通过评估熵、互信息(MI)、结构相似度(SSIM)等以及一种称为特征互信息的专门性能指标来判断融合后的图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medical Image Fusion using PCNN Optimized by Whale Optimization Algorithm
This paper proposes a novel algorithm for the fusion of medical images using a modified Pulse Coupled Neural Network(PCNN) optimized by the Whale Optimization Algorithm(WOA). In this proposed algorithm the two images are passed through the WOA which computes the necessary parameters for the PCNN feature extractor through a multi-criteria fitness function. The features thus extracted are then used to fuse the images. The resultant fused image is judged by evaluating the entropy, Mutual Information (MI), Structural Similarity (SSIM), etc. as well as a specialized performance metric called feature mutual information.
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