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Multifocus Image Fusion Based on Multiresolution Transform and Particle Swarm Optimization

机译:基于多分辨率变换和粒子群优化的多焦点图像融合

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In order to get an image with every object in focus, an image fusion process is required to fuse the images under different focal settings. In this paper, a novel multifocus image fusion algorithm based on multiresolution transform and particle swarm optimization (PSO) is proposed. Firstly the source images are decomposed into lowpass subbands coefficients and highpass subbands coefficients by the nonsubsampled contourlet transform (NSCT). Then, different fusion rules are applied for low and high frequency NSCT coefficients. Finally the fused image is reconstructed by the inverse NSCT transform. The experiment results demonstrate that the proposed method is effective and can provide better performance than the method based on the wavelet transform and the nonsubsampled contourlet transform.
机译:为了将图像与每个对象进行焦点,需要在不同的焦点设置下熔断图像来融合图像融合过程。本文提出了一种基于多分辨率变换和粒子群优化(PSO)的新型多焦点图像融合算法。首先,源图像被非管制的Contourlet变换(NSCT)分解成低通子带系数并高通频带系数。然后,应用不同的融合规则用于低频和高频NSCT系数。最后,通过逆NSCT变换重建融合图像。实验结果表明,所提出的方法是有效的,并且可以提供比基于小波变换和非管制型轮廓变换的方法更好的性能。

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