Spatially Adaptive Block-Based Super-Resolution
Super-resolution technology provides an effectiveway to increase image resolution by incorporating additionalinformation from successive input images or training samples.Various super-resolution algorithms have been proposed basedon different assumptions, and their relative performances candiffer in regions of different characteristics within a single image.Based on this observation, an adaptive algorithm is proposedin this paper to integrate a higher level image classificationtask and a lower level super-resolution process, in which weincorporate reconstruction-based super-resolution algorithms,single-image enhancement, and image/video classification intoa single comprehensive framework. The target high-resolutionimage plane is divided into adaptive-sized blocks, and differentsuitable super-resolution algorithms are automatically selected forthe blocks. Then, a deblocking process is applied to reduce blockedge artifacts. A new benchmark is also utilized to measure theperformance of super-resolution algorithms. Experimental resultswith real-life videos indicate encouraging improvements with ourmethod.
- System : Pentium Dual Core.
- Hard Disk : 120 GB.
- Monitor : 15’’LED
- Input Devices : Keyboard, Mouse
- Ram :1 GB
- Operating system : Windows 7.
- Coding Language :MATLAB
- Tool : MATLAB R2013A
Heng Su, Liang Tang, Ying Wu, Senior Member, IEEE, Daniel Tretter, and Jie Zhou, Senior Member, IEEE, “Spatially Adaptive Block-Based Super-Resolution”, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 21, NO. 3, MARCH 2012.