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Conference Paper
Adaptive Self-Similarity based Image Super-Resolution using Non Local Means
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- Authors
- Ji-Hoon Choi, Sae-Jin Park, Dae-Yeol Lee, Sung-Chang Lim, Jin-Soo Choi, Jong-Ok Kim
- Issue Date
- 2014-12
- Citation
- Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) 2014, pp.1-5
- Language
- English
- Type
- Conference Paper
- Abstract
- Self-similarity based SR method on the LF-HF domain basically relies on the assumption that LF patch is highly correlated with HF patch. However, this assumption is content-specific significantly, and we can occasionally observe little correlation between LF and HF patch especially for texture region of natural images. In this paper we propose a new self-similarity based SR method to reflect this observation. There are two differences between the proposed and existing methods. First, HF details of target HR image are recovered by finding the similar patches on the MF domain in case of texture region. Second, the proposed method performs pixel-based reconstruction by adopting the concept of non-local means. Experimental results show that the proposed method can reconstruct more realistic image details.
- KSP Keywords
- Image super-resolution, Natural images, Pixel-based, non local means, self-similarity, similar patches, texture region