TitleFiltered Mapping-Based Method for Compressed Web Image Super-Resolution
AuthorsZhao, Yang
Jia, Wei
Li, Lin
Cao, Li
Liu, Xiaoping
AffiliationHefei Univ Technol, Sch Comp & Informat, Hefei 230000, Anhui, Peoples R China.
Peking Univ, Shenzhen Grad Sch, Sch Elect & Comp Engn, Shenzhen 518055, Peoples R China.
KeywordsSuper-resolution
upsampling
deblocking
INVARIANT TEXTURE CLASSIFICATION
SINGLE-IMAGE
SPARSE REPRESENTATION
KERNEL REGRESSION
SUPER RESOLUTION
RECONSTRUCTION
INTERPOLATION
DEBLOCKING
VIDEO
Issue Date2017
PublisherIEEE ACCESS
CitationIEEE ACCESS.2017,5,12682-12695.
AbstractThe Web images and videos are often downsampled and compressed to save the bandwidth and storage. Hence, the low-quality and low-resolution Web images/videos cannot match the high-definition display devices nowadays. Unfortunately, traditional image super-resolution (SR) methods are not very robust to compression artifacts. In this paper, we propose an efficient joint SR and deblocking method based on simple three-step-process, which consists of a block-matching and 3D filtering process, a local binary encoding process, and a mapping reconstruction process. Furthermore, the cascade framework and an extra post-processing are also presented for large magnification factors. Experimental results on real-world Web images with obvious compression artifacts demonstrate that the proposed method can reproduce clear and sharp SR results, and effectively remove the unnatural artifacts at the same time.
URIhttp://hdl.handle.net/20.500.11897/475875
ISSN2169-3536
DOI10.1109/ACCESS.2017.2721458
IndexedSCI(E)
Appears in Collections:信息工程学院

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