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Technical Program
Paper Detail
| Paper: | MP-L3.3 |
| Session: | Deblurring and Image Restoration |
| Time: | Monday, October 9, 15:00 - 15:20 |
| Presentation: |
Lecture
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| Title: |
DEBLURRING-BY-DENOISING USING SPATIALLY ADAPTIVE GAUSSIAN SCALE MIXTURES IN OVERCOMPLETE PYRAMIDS |
| Authors: |
Jose A. Guerrero-Colon; Universidad de Granada | | | | | Javier Portilla; Universidad de Granada | | |
| Abstract: |
In a previous work, we presented an extension of the original Bayes Least Squares - Gaussian Scale Mixtures (BLS-GSM) denoising algorithm that also compensated the blur. However, it suffered from some weaknesses: a) it could not compensate for some blurring kernel shapes; b) its performance depended critically on an accurate estimation of the original power spectral density (PSD); and c) it could not be easily adapted to a spatially variant description of the local statistics. In this work we propose a two-step restoration method that overcomes these problems by first performing a global blur image compensation, and then applying a spatially adaptive local denoising, in an overcomplete pyramid. Our method is efficient, robust and non-iterative. We demonstrate through simulations that it provides state-of-the-art performance. |
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