Context-based adaptive image resolution upconversion

被引:8
|
作者
Shi, Guangming [1 ]
Dong, Weisheng [1 ]
Wu, Xiaolin [3 ]
Zhang, Lei [2 ]
机构
[1] Xidian Univ, Key Lab Intelligent Percept & Image Understanding, Minist Educ, Xian 710071, Peoples R China
[2] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Hong Kong, Peoples R China
[3] McMaster Univ, Dept Elect & Comp Engn, Hamilton, ON, Canada
基金
美国国家科学基金会;
关键词
INTERPOLATION;
D O I
10.1117/1.3327934
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We propose a practical context-based adaptive image resolution upconversion algorithm. The basic idea is to use a low-resolution (LR) image patch as a context in which the missing high-resolution (HR) pixels are estimated. The context is quantized into classes and for each class an adaptive linear filter is designed using a training set. The training set incorporates the prior knowledge of the point spread function, edges, textures, smooth shades, etc. into the upconversion filter design. For low complexity, two 1-D context-based adaptive interpolators are used to generate the estimates of the missing pixels in two perpendicular directions. The two directional estimates are fused by linear minimum mean-squares weighting to obtain a more robust estimate. Upon the recovery of the missing HR pixels, an efficient spatial deconvolution is proposed to deblur the observed LR image. Also, an iterative upconversion step is performed to further improve the upconverted image. Experimental results show that the proposed context-based adaptive resolution upconverter performs better than the existing methods in both peak SNR and visual quality. (C) 2010 SPIE and IS&T. [DOI: 10.1117/1.3327934]
引用
收藏
页数:9
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