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Proceedings Paper

MTF compensation algorithm based on blind deconvolution for high-resolution remote sensing satellite
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Paper Abstract

In high resolution remote sensing satellite imaging system, image restoration is an important step to visualize ne details and mitigate the noise. The raw image data often presents poor imaging quality due to various reasons and Point Spread Function (PSF) measures such blurriness characteristic of the image using point source. Satellite image from Korea Multi-purpose Satellite 2 (KOMPSAT-2) also requires Modular Transfer Function (MTF) compensation process to achieve more realistic image which entails removing ringing artifacts at the edges and restraining excess use of denoising eect in order to keep it more realistic. This paper focuses on the deconvolution of KOMPSAT-2 image utilizing PSF attained from Korea Aerospace Research Institute compared to deconvolution with the estimated PSF blur kernel. The deconvolution algorithm considered are Richard-Lucy, Damped Richard-Lucy, Bilateral Richard-Lucy and Sparse Prior deconvolution algorithms.

Paper Details

Date Published: 7 May 2012
PDF: 7 pages
Proc. SPIE 8399, Visual Information Processing XXI, 83990R (7 May 2012); doi: 10.1117/12.920877
Show Author Affiliations
Jihye Lee, KAIST (Korea, Republic of)
Joohwan Chun, KAIST (Korea, Republic of)
Donghwan Lee, Korea Aerospace Research Institute (Korea, Republic of)

Published in SPIE Proceedings Vol. 8399:
Visual Information Processing XXI
Mark Allen Neifeld; Amit Ashok, Editor(s)

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