Poisson Denoising for Astronomical Images

A denoising scheme for astronomical color images/videos corrupted with Poisson noise is proposed. The scheme employs the concept of Exponential Principal Component Analysis and sparsity of image patches. The color space RGB is converted to YCbCr and K-means++ clustering is applied on luminance compo...

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Bibliographic Details
Published inAdvances in Astronomy Vol. 2018; no. 2018; pp. 1 - 7
Main Authors Shamshad, Fahad, Ghafoor, Abdul, Mohsin Riaz, Muhammad
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 01.01.2018
Hindawi
John Wiley & Sons, Inc
Hindawi Limited
Wiley
Subjects
Algorithms
Astronomy
Clustering
Color
Color imagery
Computer simulation
Computing time
Efficiency
Hypothesis testing
Image processing
Information processing
International conferences
Noise
Noise reduction
Parameter estimation
Principal components analysis
Random variables
Signal processing
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Summary:A denoising scheme for astronomical color images/videos corrupted with Poisson noise is proposed. The scheme employs the concept of Exponential Principal Component Analysis and sparsity of image patches. The color space RGB is converted to YCbCr and K-means++ clustering is applied on luminance component only. The cluster centers are used for chromatic components to improve the computational efficiency. For videos, the information of both spatial and temporal correlations improves the denoising. Simulation results verify the significance of proposed scheme in both visual and quantitative manner.
ISSN:1687-7969
1687-7977
DOI:10.1155/2018/2417939