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Image super resolution by sparse linear regression and iterative back projection
Date Issued
2016
Publisher
IEEE
ISBN
9781467390446
9781467390453
ISSN
2155-5052
Citation
Nawaz, M., Xie, R., Zhang, L., Asfandyar, M., & Hussain, M. (2016). Image super resolution by sparse linear regression and iterative back projection. In BMSB (Ed.). 2016 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). 2016 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), Nara, Japan. IEEE.
Type
Conference Paper
Abstract
This paper presents a method which focus on the increase of visual quality of SR image reconstructed from input low resolution image. Similar to the framework as exploited in [1], a modified algorithm is developed which is based on sparse linear regression and iterative back projection. Different from the techniques used in [1] [6], a feature sign search algorithm [17] is used to find the relevant features of the regression function under a priori assumption. Furthermore, a modified Gaussian high pass filter is additionally used for the refinement of the initial reconstructed SR image through iterative back-projection technique to reduce visual artifacts. Experimental results conclude that this modified approach achieves better quality of reconstructed SR images than the other similar SR methods.
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