SoftCuts: A Soft Edge Smoothness Prior for Color Image Super-Resolution

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,...

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Bibliographic Details
Published in:IEEE transactions on image processing 2009-05, Vol.18 (5), p.969-981
Main Authors: Shengyang Dai, Mei Han, Wei Xu, Ying Wu, Yihong Gong, Katsaggelos, A.K.
Format: Article
Language:English
Subjects:
Adaptive algorithms
Algorithms
alpha -channel description
Applied sciences
Approximation
Color
Detection, estimation, filtering, equalization, prediction
edge smoothness
Exact sciences and technology
HDTV
Image analysis
Image processing
Image reconstruction
Image resolution
Information, signal and communications theory
Inverse problems
Length measurement
Mathematical analysis
Object recognition
Pattern recognition
Signal and communications theory
Signal processing
Signal, noise
Smoothness
SoftCuts
Strontium
Studies
super-resolution (SR)
Telecommunications and information theory
Video compression
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Summary: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 . 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 alpha-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.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2009.2012908