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Spatially Adaptive Block-Based Super-Resolution

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5 Author(s)
Heng Su ; Dept. of Autom., Tsinghua Univ., Beijing, China ; Liang Tang ; Ying Wu ; Tretter, D.
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Super-resolution technology provides an effective way to increase image resolution by incorporating additional information from successive input images or training samples. Various super-resolution algorithms have been proposed based on different assumptions, and their relative performances can differ in regions of different characteristics within a single image. Based on this observation, an adaptive algorithm is proposed in this paper to integrate a higher level image classification task and a lower level super-resolution process, in which we incorporate reconstruction-based super-resolution algorithms, single-image enhancement, and image/video classification into a single comprehensive framework. The target high-resolution image plane is divided into adaptive-sized blocks, and different suitable super-resolution algorithms are automatically selected for the blocks. Then, a deblocking process is applied to reduce block edge artifacts. A new benchmark is also utilized to measure the performance of super-resolution algorithms. Experimental results with real-life videos indicate encouraging improvements with our method.

Published in:

Image Processing, IEEE Transactions on  (Volume:21 ,  Issue: 3 )

Date of Publication:

March 2012

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