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

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.