Motion random exposure based super-resolution imaging system and method

Abstract

The invention discloses a motion random exposure based super-resolution imaging system and method, belonging to the technical field of image acquisition. The imaging system comprises a black box, a motion route control cableway, a low-resolution camera, an added shutter, a binary random number generator and an image reconstruction processor, wherein the low-resolution camera is fixed on the support of the motion route control cableway and moves in the black box along a given route at the fixed speed, meanwhile, the added shutter in front of a camera lens flickers under the control of the pulse signal sequences generated by the binary random number generator to carry out motion random exposure and transmits the low-resolution images obtained after exposure to the image reconstruction processor, a high-resolution image reconstruction model is established according to the sparsity of the high-resolution images, and the high-resolution images are reconstructed by a nonlinear optimization method. The invention has the advantages of simple structure, easy implementation and low cost and is used for acquisition and reconstruction of the super-resolution images.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a super-resolution image imaging system and method, which are mainly used in the acquisition and reconstruction of super-resolution images. Background technique [0002] Super-resolution images have a wide range of applications in the fields of mobile communications, image and video compression technology, social security, video surveillance, graphics rendering, image restoration, biometric authentication, satellite and astronomical images, and high-definition television. There are two main ways to obtain super-resolution images. The first method is to directly improve the accuracy of the sensor to obtain high-resolution images. Due to the limitations of processing technology and manufacturing materials, this method is difficult and costly to implement. And it is easy to bring shot noise, which seriously affects the image quality. To overcome these shortcomings,...

AI Technical Summary

Problems solved by technology

[0008] According to CS theory, under certain conditions, ultra-high resolution images can be reconstructed from few observations obtained at low sampling rates. Taking advantage of this feature, several imagers based on CS theory have been developed, such as single-pixel Camera, CMOS compression imaging system, Coded-Aperture imaging system, etc. However, these systems have common disadvantages: complex structure and difficult implementation. These defects limit their application. Can you design a simple, easy to implement and low cost Methods to obtain and reconstruct super-resolution images have become an urgent problem to be solved.

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