Image reconstruction by multiscale compressed sensing based on a new transform

Chun-hai Hu; Shi-liang Guo

doi:10.1117/12.2034497

11 September 2013 Image reconstruction by multiscale compressed sensing based on a new transform

Chun-hai Hu, Shi-liang Guo

Author Affiliations +

Proceedings Volume 8907, International Symposium on Photoelectronic Detection and Imaging 2013: Infrared Imaging and Applications; 890740 (2013) https://doi.org/10.1117/12.2034497
Event: ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, 2013, Beijing, China

Abstract

This paper proposes a multiscale deployment of Compressed Sensing(CS) in a new transform domain for image reconstruction. The new transform, directly built in the discrete framework, combines the traditional discrete wavelet transform with shearing filter banks defined in the Pseudo-Polar frequency domain to perform multiresolution and multidirectional analysis of images. Then a specific decimation way is applied to further get rid of extra redundancy with no aliasing. The proposed transform named wavelet-based discrete shearlet transform (WBDST) which can be seen as a extension of the original discrete shearlet transform is also optimally efficient in representing images containing edges while offering a dramatically low redundant property. Furthermore, we deploy a multiscale CS scheme in WBDST domain for image reconstruction, different scales are segregated and CS is applied separately to each one. Numerical experiments demonstrate that this deployment gives much better quality reconstructions than those of the WBDST based best N-term approximation as well as the curvelets based multiscale CS scheme.

Citation Download Citation

Chun-hai Hu, Chun-hai Hu, Shi-liang Guo, Shi-liang Guo, "Image reconstruction by multiscale compressed sensing based on a new transform", Proc. SPIE 8907, International Symposium on Photoelectronic Detection and Imaging 2013: Infrared Imaging and Applications, 890740 (11 September 2013); doi: 10.1117/12.2034497; https://doi.org/10.1117/12.2034497

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