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Using fuzzy logic and particle swarm optimization to design a decision-based filter for cDNA microarray image restoration

机译:使用模糊逻辑和粒子群优化设计基于决策的cDNA微阵列图像复原滤波器

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摘要

This paper presents a Decision-Based cDNA Microarray Image filter for the removal of impulse noises for complementary deoxyribonucleic acid (cDNA) microarray images. It employs Fuzzy Logic (FL) technique to design a noise detector optimized by Particle Swarm Optimization (PSO), and utilizes center weighted vector median (CWVM) filter for restoring. For convenience, it is called the DBAMI filter hereafter. The proposed filter first employs the FL technique to detect each vector-valued pixel of a cDNA microarray image. If it is considered as noise-corrupted, the DBAMI filter restores it with the CWVM filter. Otherwise, it remains unchanged. Experimental results demonstrate that the DBAMI filter outperforms the existing well-known filters in restoration of cDNA microarray images under considerations here.
机译:本文提出了一种基于决策的cDNA微阵列图像过滤器,用于去除互补脱氧核糖核酸(cDNA)微阵列图像的脉冲噪声。它采用模糊逻辑(FL)技术设计通过粒子群优化(PSO)优化的噪声检测器,并利用中心加权矢量中值(CWVM)滤波器进行恢复。为了方便起见,以下将其称为DBAMI过滤器。提出的过滤器首先采用FL技术来检测cDNA微阵列图像的每个矢量值像素。如果它被认为是噪声损坏的,则DBAMI过滤器将使用CWVM过滤器将其还原。否则,它保持不变。实验结果表明,在此处考虑的情况下,DBAMI过滤器在恢复cDNA微阵列图像方面优于现有的众所周知的过滤器。

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