Dr. Hao Bai Profile

Dr. Hao Bai

at Beijing Institute of Technology

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Proceedings Article | 5 November 2020 Paper

Block-based compressed sensing algorithm for image compressed and transmission in visible spectral remote sensing imaging system

Hao Bai, Tingzhu Bai

Proceedings Volume 11567, 1156743 (2020) https://doi.org/10.1117/12.2580291

KEYWORDS: Image compression, Remote sensing, Compressed sensing, Image processing

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High-resolution visible spectral remote sensing images enriches human cognition of the world, also brings challenges to the image storage and transmission. Traditional compression method can reduce the transmission bandwidth, also cause defects such as long computing time, high algorithm complexity, and large errors. Compressed sensing can reconstruct high-quality images which is similar with the original image. It provides a new method for remote sensing image compression and reconstruction. This paper analyzes the advantages of blockbased compressed sensing algorithm, and proves that block-based compressed sensing algorithm is superior to nonblock-based compressed sensing algorithm from the perspective of algorithm complexity. This paper modifies the smoothed projected Landweber (SPL) algorithm to make it suitable for the color image. According to the simulation results, it is obvious that the block-shaped compressed sensing algorithm can effectively reduce the transmission cost and ensure the reconstruction quality of the compressed images.

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