DocumentCode :
2169857
Title :
Self-learning-based single image super-resolution of a highly compressed image
Author :
Li-Wei Kang ; Bo-Chi Chuang ; Chih-Chung Hsu ; Chia-Wen Lin ; Chia-Hung Yeh
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Yunlin Univ. of Sci. & Technol., Douliu, Taiwan
fYear :
2013
fDate :
Sept. 30 2013-Oct. 2 2013
Firstpage :
224
Lastpage :
229
Abstract :
Low-quality images are usually not only with low-resolution, but also suffer from compression artifacts (blocking artifact is treated as an example in this paper). Directly performing image super-resolution (SR) to a highly compressed (low-quality) image would also simultaneously magnify the blocking artifacts, resulting in unpleasing visual quality. In this paper, we propose a self-learning-based SR framework to simultaneously achieve single-image SR and compression artifact removal for a highly-compressed image. We argue that individually performing deblocking first, followed by SR to an image, would usually inevitably lose some image details induced by deblocking, which may be useful for SR, resulting in worse SR result. In our method, we propose to self-learn image sparse representation for modeling the relationship between low and high-resolution image patches in terms of the learned dictionaries, respectively, for image patches with and without blocking artifacts. As a result, image SR and deblocking can be simultaneously achieved via sparse representation and MCA (morphological component analysis)-based image decomposition. Experimental results demonstrate the efficacy of the proposed algorithm.
Keywords :
data compression; image coding; image representation; image resolution; MCA-based image decomposition; blocking artifacts; compression artifacts; high-resolution image patches; highly compressed image; low-quality images; morphological component analysis-based image decomposition; self-learn image sparse representation; self-learning-based SR framework; self-learning-based single image super-resolution; single-image SR artifact removal; single-image compression artifact removal; visual quality; Dictionaries; Image coding; Image decomposition; Image reconstruction; Image resolution; Interpolation; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Signal Processing (MMSP), 2013 IEEE 15th International Workshop on
Conference_Location :
Pula
Type :
conf
DOI :
10.1109/MMSP.2013.6659292
Filename :
6659292
Link To Document :
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