Name
Abstract | ||
|---|---|---|
Image blind restoration has been a significant subject in various application fields. In the paper, we mainly studied the color image. In the process of converting color image into gray image will result in the loss of information because color image has different channels. In order to solve blind deconvolution of color image effectively, we present a method that estimates kernel result from three channels of color image directly based on multiscale framework. And then we use the Multichannel Total Variation (MTV) model to protect image edges. By using normalized hyper Laplacian prior term, our method can converge to the real solution. The final clear image can be gotten. Although the MTV model will increase the complexity of computation, The correctness of algorithm and the feasibility of methods are proved by experiments. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CISP-BMEI.2017.8301961 | 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) |
Keywords | Field | DocType |
motion deblurring,blind deconvolution,the MTV model,color image | Kernel (linear algebra),Computer vision,Normalization (statistics),Pattern recognition,Blind deconvolution,Deblurring,Computer science,Deconvolution,Artificial intelligence,Image restoration,Color image,Computation | Conference |
ISBN | Citations | PageRank |
978-1-5386-1938-4 | 0 | 0.34 |
References | Authors | |
7 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong Zhang | 1 | 276 | 26.98 |
| Guodong Wang | 2 | 5 | 2.78 |
| Nan Wu | 3 | 0 | 0.68 |
| Guojia Hou | 4 | 24 | 6.41 |
| Zhimei Zhang | 5 | 0 | 0.68 |