Abstract
Background/Objectives: This study presents an external and internal prior guided patch based filter for minimizing Gaussian noise in complementary deoxyribonucleic acid (cDNA) microarray images. Methods/Statistical analysis: The proposed denoising filter is capable of taking into consideration both external and internal prior. It employs combined prior guided patch based denoising considering various distance based patch-matching methods. Findings: Experimental results demonstrate that the combined prior guided patch based filter outperforms the existing well-known filters in minimizing noise of cDNA microarray images. The outcome of the proposed scheme found to offer better peak signalto-noise ratio and structural similarity index in contrast to existing filtering techniques. Effectiveness of the proposed denoising method is also assessed by estimating the spot intensities of cDNA microarray image that reflects the effect of noise reduction in the image. Application/Improvements: Minimization of noise is a crucial step of cDNA microarray image processing and it aids in microarray analysis by extracting valid and good quality gene expression measurements. Keywords: Denoising, External Prior, Internal Prior, K- nearest Neighbor, Microarray Image, Singular Value Decomposition
Highlights
Microarray imaging technology has shown major progress in genomic research by allowing molecular biologists to monitor thousands of expression levels of genes at a time
An image denoising framework that integrates internal prior learned from noisy image as well as prior learned from the dataset is proposed in this article
Algorithm implementation depends on parameters signal to noise ratio of noisy patch, median of the noisy image to increase the effectiveness in search of reference patches from noisy image
Summary
Microarray imaging technology has shown major progress in genomic research by allowing molecular biologists to monitor thousands of expression levels of genes at a time. The method of Chang[4] proposes decision based filter for the elimination of impulse noises in cDNA microarray images. Patch level-based filtering offers good methodology to minimize the presence of noise It shows an increase in performance when noise level is less and results in a smoother denoised image for higher noise level. By adding various types and amounts of noise that characterize biological and measurement errors to the simulated images, performance of the proposed algorithm can be effectively tested. This can give a significant understanding of the efficiency of the algorithms
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