Volume 43 Issue 1
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JOURNAL OF MECHANICAL ENGINEERING  > 2017  >  43(1): 43-48.
DU Weinan, HU Yongli, SUN Yanfeng. Image Super-resolution Reconstruction Based on Residual Dictionary Learning[J]. JOURNAL OF MECHANICAL ENGINEERING, 2017, 43(1): 43-48. doi: 10.11936/bjutxb2016060049
Citation: DU Weinan, HU Yongli, SUN Yanfeng. Image Super-resolution Reconstruction Based on Residual Dictionary Learning[J]. JOURNAL OF MECHANICAL ENGINEERING, 2017, 43(1): 43-48. doi: 10.11936/bjutxb2016060049
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Image Super-resolution Reconstruction Based on Residual Dictionary Learning

doi: 10.11936/bjutxb2016060049

  • Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing 100124, China

  • Received Date: 16 Jun 2016
    Available Online: 09 Sep 2022
  • Issue Publish Date: 01 Jan 2017
    Abstract
  • In this paper, an image super-resolution method was proposed based on 2D separable dictionary and residual dictionary to improve the quality of reconstructed image and to preserve space information as well as high-frequency information. Unlike the conventional super-resolution method based on 1D dictionary, the 2D separable dictionary was constructed from a set of training images in 2D matrix form without vectorization, so it had the capacity of learning the inherent texture structure of images. Additionally, it was a pair of compact dictionaries that were of smaller size and less storage space compared with the conventional dictionary. To restore more high-frequency information, the residual dictionary was introduced based on the reconstructed images with the 2D separable dictionary, which captured the high-frequency information of edges, angles and corners in images. Combining the two dictionary learning procedures into one framework, the proposed method was expected to synthesize high resolution images with high quality. The proposed algorithm was tested on public natural image set. The experiment results show that the proposed image super-resolution method based on 2D separable dictionary and residual dictionary is effective and superior.

     

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