Multi-shot encoded compressive imaging method for super-resolution

Juan Du; Xiao-peng Shao; Cheng Zhong

doi:10.1117/12.2034882

30 August 2013 Multi-shot encoded compressive imaging method for super-resolution

Juan Du, Xiao-peng Shao, Cheng Zhong

Proceedings Volume 8910, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications; 89101W (2013) https://doi.org/10.1117/12.2034882
Event: ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, 2013, Beijing, China

Abstract

The compressed coded aperture imaging method based on Compressed Sensing theory is developed to acquire high resolution image from a low resolution Focal Plane Array (FPA) device using Super Resolution (SR) reconstruction algorithms, which makes it possible to sample fewer points and reconstruct high resolution images. However, a lot of problems remain unsolved in this field. Aiming at realizing the super resolution imaging with multiple random samplings by using a low resolution optical sensor, a novel architecture of multi-shot compressed coded aperture imaging (MCCAI) is proposed in the paper. Based on the classical ℓ₂ -ℓ₁ optimization model, the high frequency information of the reconstructed image is reserved. Although the low-frequency components which should be smooth are mixed with high frequency components, which is displayed as the artifacts that arise in the process of the image reconstruction. With the purpose of solving this problem, a regular term of total variation is appended to the original optimization. The improved ℓ₂ -ℓ₁ -TV optimization model can save the high frequency of the scene in the largest degree, and at the same time reduce the artifacts, which can dramatically improve the quality of the reconstructed image. Using the two optimization model, three different images are tested, and the experimental results show that comparing with the ℓ₂ -ℓ₁ optimization model, the ℓ₂ -ℓ₁ -TV optimization model can improve the image quality of the compressed coded aperture effectively and eliminate the artifacts while retaining the original information of the signals and improving the SNR (signal-to-noise ratio).

Citation Download Citation

Juan Du, Xiao-peng Shao, and Cheng Zhong "Multi-shot encoded compressive imaging method for super-resolution", Proc. SPIE 8910, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications, 89101W (30 August 2013); https://doi.org/10.1117/12.2034882

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KEYWORDS

Image processing

Coded aperture imaging

Image resolution

Optimization (mathematics)

Super resolution

Reconstruction algorithms

Simulation of CCA and DLA aggregates

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