A compression imaging system and method based on multi-channel image acquisition

Abstract

The invention discloses a compressed imaging system and method based on multi-channel image acquisition, which processes an input imaging target into a compressed measurement value output; it includes a multi-channel optical imaging system, a coding mask generation module, a CMOS image sensor pixel array module, Scalable readout circuit and A / D conversion module; realize multi-channel optical imaging of the imaging target, and generate multiple similar multi-channel acquisition images; optically modulate the multi-channel acquisition images by the encoding mask generation module, once The CMOS image sensor pixel array module converts all the light domain measurement values ​​generated through the encoding mask into electrical analog signals; the CMOS image sensor is read out by a scalable readout circuit Part of the electrical analog measurement of the pixel array; performing an A / D conversion of the electrical analog measurement. The invention proposes a novel compression imaging system with low power consumption, block parallel measurement and scalable compression rate.

Description

technical field [0001] The invention relates to the field of digital image acquisition and processing in multimedia, in particular to a compressed imaging system and method. Background technique [0002] Traditional image signal acquisition and processing is based on the Shannon sampling theorem. Its high-speed sampling and then compression processing method causes a lot of waste of sampling resources, additionally increases the burden of the photoelectric detection array, and the coding complexity is high. In situations where detectors are expensive such as THz imaging, reducing the number of photodetectors can effectively reduce the manufacturing cost of the entire system; in applications powered by batteries such as wireless sensor network nodes and mobile multimedia terminals, power consumption is severely limited , low-complexity coding, and smaller photodetection imaging arrays are beneficial to reduce its energy consumption and prolong its working time. [0003] The ...

AI Technical Summary

Problems solved by technology

Compared with traditional imaging methods, CI can compress and sample targets with fewer detectors, effectively improve the measurement accuracy of limited noise detectors, and has low imaging complexity, which is suitable for applications where power consumption is limited. The research on compressed imaging is still in its infancy, and there are few related research results at home and abroad.

The "single-pixel camera" proposed by Rice University is a good verification of the compression imaging theory, but it is expensive, large in size, and slow in imaging speed; the CI system based on compression coded aperture adopts parallel measurement method, although in terms of imaging speed It has been improved, but it cannot perform block-based compression measurement, which seriously affects the reconstruction speed of the original image, and can only perform compressed imaging at a single bit rate, which cannot adapt well to changes in the environment

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