Reducible dictionaries for single image super-resolution based on patch matching and mean shifting

Pejman Rasti; Kamal Nasrollahi; Olga Orlova; Gert Tamberg; Thomas B. Moeslund; Gholamreza Anbarjafari

doi:10.1117/1.JEI.26.2.023024

22 April 2017 Reducible dictionaries for single image super-resolution based on patch matching and mean shifting

Pejman Rasti, Kamal Nasrollahi, Olga Orlova, Gert Tamberg, Thomas B. Moeslund, Gholamreza Anbarjafari

Author Affiliations +

Journal of Electronic Imaging, Vol. 26, Issue 2, 023024 (April 2017). https://doi.org/10.1117/1.JEI.26.2.023024

Abstract

A single-image super-resolution (SR) method is proposed. The proposed method uses a generated dictionary from pairs of high resolution (HR) images and their corresponding low resolution (LR) representations. First, HR images and the corresponding LR ones are divided into patches of HR and LR, respectively, and then they are collected into separate dictionaries. Afterward, when performing SR, the distance between every patch of the input LR image and those of available LR patches in the LR dictionary is calculated. The minimum distance between the input LR patch and those in the LR dictionary is taken, and its counterpart from the HR dictionary is passed through an illumination enhancement process. By this technique, the noticeable change of illumination between neighbor patches in the super-resolved image is significantly reduced. The enhanced HR patch represents the HR patch of the super-resolved image. Finally, to remove the blocking effect caused by merging the patches, an average of the obtained HR image and the interpolated image obtained using bicubic interpolation is calculated. The quantitative and qualitative analyses show the superiority of the proposed technique over the conventional and state-of-art methods.

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Pejman Rasti, Kamal Nasrollahi, Olga Orlova, Gert Tamberg, Thomas B. Moeslund, and Gholamreza Anbarjafari "Reducible dictionaries for single image super-resolution based on patch matching and mean shifting," Journal of Electronic Imaging 26(2), 023024 (22 April 2017). https://doi.org/10.1117/1.JEI.26.2.023024

Received: 24 December 2016; Accepted: 7 April 2017; Published: 22 April 2017

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