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Super-Resolution Image Reconstruction Using Wavelet Based Patch and Discrete Wavelet Transform

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Abstract

This paper proposes a novel method that combines the discrete wavelet transform (DWT) and example-based technique to reconstruct a high-resolution from a low-resolution image. Although previous interpolation- and example-based methods consider the reconstruction adaptive to edge directions, they still have a problem with aliasing and blurring effects around edges. In order to address these problems, in this paper, we utilize the frequency sub-bands of the DWT that has the feature of lossless compression. Our proposed method first extracts the frequency sub-bands (Low-Low, Low-High, High-Low, High-High) from an input low-resolution image by the DWT, and then the low-resolution image is inserted into the Low-Low sub-band. Since information in high-frequency sub-bands (Low-High, High-Low, and High-High) might be lost in the low-resolution image, they are reconstructed or estimated by using example-based method from image patch database. After that, we make a high-resolution image by performing the inverse DWT of reconstructed frequency sub-bands. In experimental results, we can show that the proposed method outperforms previous approaches in terms of edge enhancement, reduced aliasing effects, and reduced blurring effects.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Hanyang University, Ansan, Republic Korea

    Do Kyung Shin & Young Shik Moon

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  1. Do Kyung Shin
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  2. Young Shik Moon
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Correspondence to Young Shik Moon.

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Shin, D.K., Moon, Y.S. Super-Resolution Image Reconstruction Using Wavelet Based Patch and Discrete Wavelet Transform. J Sign Process Syst 81, 71–81 (2015). https://doi.org/10.1007/s11265-014-0903-2

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  • DOI: https://doi.org/10.1007/s11265-014-0903-2

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