Name
Abstract | ||
|---|---|---|
To solve the image deblurring problem, most of the recently proposed nonblind deblurring approaches focus on regularizing the solutions by adding image priors, such as sparse prior, piece-wise smooth prior (total-variation prior), and so on. This paper, however, presents a new term, which can be viewed as a supplement to the data fidelity term, to improve the nonblind deblurring result. The new term is based on the relative error in frequency domain (REFD) and can suppress the ringing artifacts and preserve the image details. We analyze the properties of REFD for image deconvolution; then, a nonblind image deconvolution algorithm is proposed via introducing the REFD term into the image deconvolution model. The experimental results demonstrate the performance and efficacy of our proposed algorithm when compared to some other state-of-the-art algorithms. (C) 2014 SPIE and IS&T |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1117/1.JEI.23.1.013015 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
image deblurring,relative error in frequency domain,weighted sub-band,ringing artifacts | Frequency domain,Ringing artifacts,Computer vision,Pattern recognition,Deblurring,Blind deconvolution,Computer science,Deconvolution,Artificial intelligence,Prior probability,Approximation error,Wavelet | Journal |
Volume | Issue | ISSN |
23 | 1 | 1017-9909 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhihui Li | 1 | 1 | 0.36 |
| S. Peng | 2 | 332 | 40.36 |
| Xiyuan Hu | 3 | 108 | 19.03 |
| Xiaojing Xu | 4 | 1 | 0.36 |