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Blind multi-image super-resolution based on combination of ANN learning and non-subsampled Contourlet directional image representation

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Abstract

In image super-resolution technique, it is contradictory to keep the edge characteristics of the image while de-noising. In order to solve the above problem, we propose a blind multi-image super-resolution algorithm which is adaptive to the image content and does not need the fuzzy conditions of generating the low-resolution images. The initially estimated high-resolution image \(\left( \hat{H}\right) \) is firstly gotten through the traditional reconstruction algorithm. Afterward, the estimation differences of low-resolution images are utilized as the input of artificial neural network (ANN), and the band-pass directional sub-bands of non-subsampled Contourlet transform (NSCT) of the lost high-frequency components are outputted in ANN. With the inverse NSCT, we can get the estimated lost high-frequency components. Finally, the estimated lost high-frequency components and the adaptive weighted matrix generated from the image content are multiplied before being added to \(\hat{H}\). Experimental results show that the high-resolution images obtained through the proposed method can achieve favorable subjective and objective quality for different image contents. Meantime, it is superior to some of the state-of-the-art classical methods in terms of the performance.

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Acknowledgements

This work was jointly supported by the National Natural Science Foundation of China (No. 61201347), Chongqing Foundation and Advanced Research Project (No. cstc2016jcyjA0103), the Natural Science Foundation Project of CQ CSTC (No. cstc2012jjA40011), and the Fundamental Research Funds for the Central Universities (No. CDJZR13185502). The support is gratefully acknowledged.

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Authors and Affiliations

  1. College of Communication Engineering, Chongqing University, Chongqing, China

    Zhiyong Shi, Fengchun Tian & Jian Ran

  2. Chongqing Communication Institute, Chongqing, China

    Zhiyong Shi & Yande Wang

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  1. Zhiyong Shi
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  2. Fengchun Tian
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Correspondence to Fengchun Tian.

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Shi, Z., Tian, F., Wang, Y. et al. Blind multi-image super-resolution based on combination of ANN learning and non-subsampled Contourlet directional image representation. SIViP 12, 25–31 (2018). https://doi.org/10.1007/s11760-017-1126-3

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  • DOI: https://doi.org/10.1007/s11760-017-1126-3

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