4.7 Article

Research on Photon-Integrated Interferometric Remote Sensing Image Reconstruction Based on Compressed Sensing

Journal

REMOTE SENSING
Volume 15, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/rs15092478

Keywords

remote sensing image; compressed sensing; image reconstruction; photon-integrated technology; detection image

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Achieving high-resolution remote sensing images is a crucial goal in space exploration. However, traditional compressed sensing with the orthogonal matching pursuit (OMP) algorithm leads to low-quality remote sensing images. This limitation in the reconstruction of sparse signals collected by photon-integrated interferometric imaging detectors hampers the advancement of photon-integrated interferometric remote sensing detection and imaging technology. By improving the OMP algorithm and introducing a threshold limited-generalized orthogonal matching pursuit (TL-GOMP) algorithm, we achieved an 18.02% increase in peak signal-to-noise ratio value (P-SNR) and a 53.62% decrease in mean square error (M-SE) in image reconstruction compared to the OMP algorithm. The TL-GOMP algorithm shows great potential in high-quality image reconstruction and its applications in photonic integrated interferometric remote sensing detection and imaging.
Achieving high-resolution remote sensing images is an important goal in the field of space exploration. However, the quality of remote sensing images is low after the use of traditional compressed sensing with the orthogonal matching pursuit (OMP) algorithm. This involves the reconstruction of the sparse signals collected by photon-integrated interferometric imaging detectors, which limits the development of detection and imaging technology for photon-integrated interferometric remote sensing. We improved the OMP algorithm and proposed a threshold limited-generalized orthogonal matching pursuit (TL-GOMP) algorithm. In the comparison simulation involving the TL-GOMP and OMP algorithms of the same series, the peak signal-to-noise ratio value (P-SNR) of the reconstructed image increased by 18.02%, while the mean square error (M-SE) decreased the most by 53.62%. The TL-GOMP algorithm can achieve high-quality image reconstruction and has great application potential in photonic integrated interferometric remote sensing detection and imaging.

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