標題: Image super-resolution by estimating the enhancement weight of self example and external missing patches
作者: Lin, Fang-Ju
Chuang, Jen-Hui
資訊工程學系
Department of Computer Science
關鍵字: Image super-resolution;Enhancement weight;Patch clustering;External superresolution
公開日期: 1-八月-2018
摘要: Image super-resolution (SR) is the process of generating a high-resolution (HR) image using one or more low-resolution (LR) inputs. Many SR methods have been proposed, but generating the small-scale structure of an SR image remains a challenging task. We hence propose a single-image SR algorithm that combines the benefits of both internal and external SR methods. First, we estimate the enhancement weights of each LR-HR image patch pair. Next, we multiply each patch by the estimated enhancement weight to generate an initial SR patch. We then employ a method to recover the missing information from the high-resolution patches and create that missing information to generate a final SR image. We then employ iterative back-projection to further enhance visual quality. The method is compared qualitatively and quantitatively with several state-of-the-art methods, and the experimental results indicate that the proposed framework provides high contrast and better visual quality, particularly for non-smooth texture areas.
URI: http://dx.doi.org/10.1007/s11042-017-5350-1
http://hdl.handle.net/11536/147950
ISSN: 1380-7501
DOI: 10.1007/s11042-017-5350-1
期刊: MULTIMEDIA TOOLS AND APPLICATIONS
Volume: 77
起始頁: 19071
結束頁: 19087
顯示於類別:期刊論文