Irrespective of certain major advancement in filtering process in medical images, the denoising operation in microarray images are still considered to be unsolved and offers a large scope of research. Existing denoising principles are less investigated on such complex and massive dimensional microarray image that leads to the development of the proposed system. We present a method of performing simple denoising operation considering the presence of Gaussian noise in microarray image. From the target image denoising method, an improved version of patch-based denoising approach has been developed considering various forms of distance-based matching methods. The study outcome of the proposed system has been found to offer better peak signal-to-noise ratio and structural similarity index in contrast to existing filtering techniques.
CITATION STYLE
Elavaar Kuzhali, S., & Suresh, D. S. (2019). Patch-based denoising with K-nearest neighbor and SVD for microarray images. In Advances in Intelligent Systems and Computing (Vol. 763, pp. 132–147). Springer Verlag. https://doi.org/10.1007/978-3-319-91186-1_15
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