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Cluster Computing

Erschienen in:

16.03.2018

Patch based fast noise level estimation using DCT and standard deviation

verfasst von: S. B. Mohan, T. A. Raghavendiran, R. Rajavel

Erschienen in: Cluster Computing | Sonderheft 6/2019

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Abstract

Image noise level estimation play a vital role in image processing applications such as medical imaging and celestial imaging. The noise level estimation of image is hard to estimate due to texture of image. Conventional methods segment image in blocks to identify noise in image. The method provides erroneous noise detection in high textured image such as medical images. In this paper, we propose a Patch based DCT (PDCT) model to decompose image in spatial domain in parallel pool loop for medical image slices. The PDCT model split noisy image into patches to exhibit noise in image. The PDCT model estimates noise level accurately in complex images compared to conventional noise level estimation methods such as principle component analysis and weak textured patch methods.

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Titel: Patch based fast noise level estimation using DCT and standard deviation
verfasst von: S. B. Mohan
T. A. Raghavendiran
R. Rajavel
Publikationsdatum: 16.03.2018
Verlag: Springer US
Erschienen in: Cluster Computing / Ausgabe Sonderheft 6/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-018-2327-4

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