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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Weiwei Li Ting Jiang Ning Wang |
| Copyright Year | 2015 |
| Description | Author affiliation: Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China (Weiwei Li; Ting Jiang; Ning Wang) |
| Abstract | Compressed Sensing (CS) theory has recently received amount of attention in the image compression filed. The sparser the signal has, the better the performance recovery. Most wavelet-based reconstruction methods of CS are developed under the assumption that the small wavelet coefficients are close to zero. In other words, a part of image information has been lost before measurement sampling. As we know, most of images have many similar areas. In order to avoid the image information being lost as little as possible, in this paper, a new CS scheme based on the similarity of image blocks is proposed in wavelet domain. Instead of processing the image as a whole, the image is firstly divided into small image blocks. And a clustering algorithm is presented to gather the similar image blocks into a group. Experiments on images demonstrate favorable performances of the proposed method. |
| Starting Page | 265 |
| Ending Page | 270 |
| File Size | 580116 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479984060 |
| DOI | 10.1109/WCNC.2015.7127480 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-03-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wavelet coefficients Clustering algorithms Discrete wavelet transforms Histograms Image coding Algorithm design and analysis Image reconstruction similarity Compressed Sensing (CS) Discrete Wavelet Transform (DWT) clustering algorithm |
| Content Type | Text |
| Resource Type | Article |
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