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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Tao Wang Yan Zhang Yong-Sheng Zhang Li-Xia Lin |
| Copyright Year | 2007 |
| Description | Author affiliation: Zhengzhou Inst. of Surveying & Mapping, Zhengzhou (Tao Wang; Yan Zhang; Yong-Sheng Zhang; Li-Xia Lin) |
| Abstract | Image superresolution (SR) reconstruction refers to methods that increase image spatial resolution by fusing information from either a sequence of temporal adjacent images or multi-source images from different sensors. In the paper we propose a hybrid MAP-POCS method for automatic image SR reconstruction, which firstly estimates the unknown point spread function (PSF) and an approximation for the original ideal image, and then sets up the HMRF image prior model and assesses its inhomogeneous control parameter through maximum likelihood (ML) estimation, finally automatically computes the regularized solution by two-phase iterative solution. Hybrid MAP-POCS estimates computed on simulation images, actual video sequence and actual satellite images show dramatic visual and quantitative improvements over bilinear interpolation and ML-POCS reconstruction results with sharp edges, correctly restored textures and a high PSNR improvement. |
| Starting Page | 426 |
| Ending Page | 431 |
| File Size | 1364052 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424410651 |
| DOI | 10.1109/ICWAPR.2007.4420706 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-11-02 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Maximum likelihood estimation Image resolution Computational modeling Video sequences low-resolution (LR) Image reconstruction Strontium Image sensors superresolution(SR) Automatic control reconstruction spatial resolution Iterative methods Spatial resolution High-resolution (HR) |
| Content Type | Text |
| Resource Type | Article |
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