Abstract:
Recently, single image super-resolution (SISR) is very important research field to reconstruct a high-resolution (HR) image from a low-resolution (LR) image. However, exi...Show MoreMetadata
Abstract:
Recently, single image super-resolution (SISR) is very important research field to reconstruct a high-resolution (HR) image from a low-resolution (LR) image. However, existing image super-resolution approaches require a lot of computations or consider parameters for various situations. This paper proposes an efficient and simple image super-resolution technique using multiple directional lapped orthogonal transforms (M-DirLOTs). It captures high-frequency informations, e.g. edges and slant textures, of images efficiently, and reduce the computational cost. Simultaneously, this model avoids any a priori hypotheses on the LR picture. The proposed method overcomes some disadvantages of existing methods. Experimental results show that the proposed method is able to significantly improve the superresolution performance.
Date of Conference: 25-28 September 2016
Date Added to IEEE Xplore: 19 August 2016
ISBN Information:
Electronic ISSN: 2381-8549