Fig. 1.
The flow chart of ICBI.
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| Citation: |
Shaosheng Dai, Junjie Cui, Dezhou Zhang, Qin Liu, Xiaoxiao Zhang. Study on infrared image super-resolution reconstruction based on an improved POCS algorithm[J]. Journal of Semiconductors, 2017, 38(4): 044010. doi: 10.1088/1674-4926/38/4/044010
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S S Dai, J J Cui, D Z Zhang, Q Liu, X X Zhang. Study on infrared image super-resolution reconstruction based on an improved POCS algorithm[J]. J. Semicond., 2017, 38(4): 044010. doi: 10.1088/1674-4926/38/4/044010.
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Study on infrared image super-resolution reconstruction based on an improved POCS algorithm
DOI: 10.1088/1674-4926/38/4/044010
More Information
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Abstract
Aiming at the disadvantages of the traditional projection onto convex sets of blurry edges and lack of image details, this paper proposes an improved projection onto convex sets (POCS) method to enhance the quality of image super-resolution reconstruction (SRR). In traditional POCS method, bilinear interpolation easily blurs the image. In order to improve the initial estimation of high-resolution image (HRI) during reconstruction of POCS algorithm, the initial estimation of HRI is obtained through iterative curvature-based interpolation (ICBI) instead of bilinear interpolation. Compared with the traditional POCS algorithm, the experimental results in subjective evaluation and objective evaluation demonstrate the effectiveness of the proposed method. The visual effect is improved significantly and image detail information is preserved better.-
Keywords:
- POCS,
- infrared image,
- super-resolution,
- initial estimation
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References
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