Compression imaging system based on separated two-dimensional compression sensing principle

Abstract

The invention discloses a compression imaging system based on a separated two-dimensional compression sensing principle. With the adoption of the imaging system, a sequential structure is adopted to produce an image on a digital micro-mirror device (DMD) through a focusing lens; line information of the image is treated by controlling a micro-mirror angle of the DMD through a constructed random line measurement matrix; the obtained line information is focused on a linear CMOS (complementary metal-oxide-semiconductor transistor) image sensor through a micro-mirror array; column information of the image is processed by means that the CMOS sensor is controlled to carry out pixel read by the constructed random column measurement matrix, so that a primary imaging process is realized, and compression information of the image is obtained through an imaging process with a certain frequency, so that the entire compression imaging process can be completed. The compression imaging system has the advantages of rapid imaging speed and strong anti-jamming capability and can provide a new method for imaging in a severe environment and imaging in an encrypted manner.

Description

[0001] This application was supported by the Tianjin Youth Fund (12JCQNJC00400); Tianjin Higher Education Science and Technology Development Fund Project (20100716). technical field [0002] The invention relates to a compressed imaging system based on compressed sensing theory, which belongs to the field of imaging suitable for harsh environments and encrypted compressed imaging. Background technique [0003] Compressed sensing theory points out that as long as the signal is sparse or compressible, the high-dimensional signal can be projected onto a low-dimensional space through a random measurement matrix unrelated to the sparse transformation basis, and then by solving an optimization problem, these small The original signal is reconstructed from the projection. Under this theoretical framework, the sampling frequency is no longer determined by the bandwidth of the signal, but by the structure and content of the information in the signal; and the compressed sensing theory...

AI Technical Summary

Problems solved by technology

[0004] The few existing compressed imaging systems based on compressed sensing theory mainly adopt sequential structure and parallel structure, but the former requires a long measurement time for large-scale images, has large measurement noise, and has poor practicability

Although the imaging speed of the latter is fast, the imaging system needs to be calibrated in advance, the process is more complicated, and the amount of calculation is large; and in order to realize large-scale image imaging, the imaging system has a large structure and is difficult to be practical

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