Open AccessA comparison between PCA and some enhancement filters for denoising astronomical images
Author(s) -
Loay Kadom Abood,
Raaid N. Hassan
Publication year - 2019
Publication title -
iraqi journal of physics
Language(s) - English
Resource type - Journals
eISSN - 2664-5548
pISSN - 2070-4003
DOI - 10.30723/ijp.v11i22.356
Subject(s) - non local means , pixel , noise reduction , artificial intelligence , filter (signal processing) , pattern recognition (psychology) , mathematics , principal component analysis , median filter , video denoising , grayscale , computer science , noise (video) , computer vision , wiener filter , gaussian noise , image (mathematics) , image denoising , image processing , video tracking , object (grammar) , multiview video coding
This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.
Experimental results shows LPG-PCA method gives better performance, especially in image fine structure preservation, compared with other general denoising algorithms.