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SoftCuts: A Soft Edge Smoothness Prior for Color Image Super-Resolution (2009)
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BibTeX
@MISC{Dai09softcuts:a,
author = {Shengyang Dai and Mei Han and Wei Xu and Ying Wu and Yihong Gong and Aggelos K. Katsaggelos},
title = {SoftCuts: A Soft Edge Smoothness Prior for Color Image Super-Resolution},
year = {2009}
}
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Abstract
Designing effective image priors is of great interest to image super-resolution (SR), which is a severely under-determined problem. An edge smoothness prior is favored since it is able to suppress the jagged edge artifact effectively. However, for soft image edges with gradual intensity transitions, it is generally difficult to obtain analytical forms for evaluating their smoothness. This paper characterizes soft edge smoothness based on a novel SoftCuts metric by generalizing the Geocuts method [1]. The proposed soft edge smoothness measure can approximate the average length of all level lines in an intensity image. Thus, the total length of all level lines can be minimized effectively by integrating this new form of prior. In addition, this paper presents a novel combination of this soft edge smoothness prior and the alpha matting technique for color image SR, by adaptively normalizing image edges according to their-channel description. This leads to the adaptive SoftCuts algorithm, which represents a unified treatment of edges with different contrasts and scales. Experimental results are presented which demonstrate the effectiveness of the proposed method.
Keyphrases
soft edge smoothness prior color image super-resolution soft edge smoothness level line soft image edge novel combination image super-resolution average length color image sr new form alpha matting technique edge smoothness different contrast adaptive softcuts algorithm intensity image normalizing image total length great interest under-determined problem novel softcuts jagged edge artifact their-channel description experimental result effective image prior unified treatment gradual intensity transition analytical form soft edge smoothness measure geocuts method
