Total-variation regularization and variable splitting-based lens-less imaging rapid reconstruction method

Abstract

The invention discloses a total-variation regularization and variable splitting-based lens-less imaging rapid reconstruction method. Aiming at a thought that image reconstruction problems of lens-lessimaging systems adopt total-variation regularization and variable splitting, a to-be-solved target function is split to two sub-problems, and the sub-problems are alternately solved to obtain a finalresult. The method comprises the following steps of: firstly importing a total-variation regularization image reconstruction model according to a linear imaging mechanism in lens-less imaging; importing an auxiliary variable and splitting the to-be-solved target function into the two sub-problems by using a variable splitting method; solving the two sub-problems by using Tikhonov regularization and anisotropic total-variation (TV) regularization; and finally alternately solving the two sub-problems so as to obtain an optimum solution. According to the method, lens-less image reconstruction can be stably carried out under unsatisfactory factors, noises can be effectively removed, and detailed information such as edges and the like of reconstructed images can be kept at the same time.

Description

technical field [0001] The invention relates to the field of lensless encoding plate imaging systems, in particular to an image reconstruction technology based on full variation regularization and variable splitting. Background technique [0002] In recent years, the emergence of novel imaging applications has driven the development of lensless imaging systems. The main research direction of lensless imaging system is coded aperture (also known as code plate) imaging, which was first used in X-ray and Gamma light imaging in astronomy, and it is usually difficult to manufacture imaging lenses suitable for such light Achieved. In recent years, some researchers have proposed lensless imaging systems for visible spectrum and infrared spectrum, and their application scenarios vary with the type of encoding plate and imaging principle. Compared with traditional lens-based cameras, the lensless imaging system has its unique advantages, such as the imaging device can be made very ...

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Problems solved by technology

[0004] The existing lensless imaging system reconstruction methods are mainly based on Tikhonov [1.Deweert M J, Farm BP.Lensless coded aperture imaging with separable doubly Toeplitz masks[J].Optical Engineering,2015,54(2):023102 .], [2.Asif M S, Ayremlou A, Sankaranarayanan A, et al.FlatCam: Thin, Lensless Cameras Using Coded Aperture and Computation[J].IEEE Transactions on Computational Imaging,2017,3(3):384-397] regular This reconstruction technique enables image reconstruction to be carried out without ideal factors (such as transformation matrix Φ L and Φ R Sickness, system noise, etc.) in the presence of stability, and does not require iteration, the reconstruction speed is fast, but the noise cannot be effectively removed, and the quality of the reconstruction is poor

Although existing denoising techniques (such as BM3D) can be used to remove noise after reconstruction, it is easy to lose details such as image edges.

In addition, the traditional full variational regularization based on partial differential equations can also be used for image reconstruction of lensless imaging systems, and can effectively preserve edge information, but the number of iterations is large, the reconstruction time is slow, and the image smooth area cannot be effectively removed noise

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