Texture preserving multi frame super resolution with spatially varying image prior

This paper proposes a new maximum a posteriori (MAP) based super-resolution (SR) image reconstruction method targeting edges and textures in images. Unlike conventional MAP based SR image reconstruction methods a spatially varying image prior is employed which is updated according to the frequency c...

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Bibliographic Details
Main Authors: Turgay, E., Akar, G. B.
Format: Conference Proceeding
Language:English
Subjects:
Bayesian
DCT
Discrete cosine transforms
Estimation
Gabor
Image edge detection
Image reconstruction
Image resolution
Image restoration
PSNR
Super Resolution
Texture
Online Access:Request full text
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Description
Summary:This paper proposes a new maximum a posteriori (MAP) based super-resolution (SR) image reconstruction method targeting edges and textures in images. Unlike conventional MAP based SR image reconstruction methods a spatially varying image prior is employed which is updated according to the frequency content of the reconstructed image at each iteration at different locations. Two alternative methods based on discrete cosine transforms (DCT) and Gabor filters are proposed for determining the image prior. The proposed method is validated through simulations and real experiments which clearly demonstrates significant visual improvements especially on edges and textures compared to state-of-the-art SR methods.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2012.6467332