Patent ID: 11899354
Assignee: EAST CHINA NORMAL UNIVERSITY
Field: Audio-visual technology (Electrical engineering)
Classification: CPC G  H | IPC G  H

Claim 4:
5. The ultrafast photographing apparatus based on polarization-time mapping according to claim 1, wherein the data reconstruction system (400) is configured to execute an iterative Tikhonov regularization algorithm by a computer, specifically comprising the following steps: setting a data acquisition process as follows:

E(m,n)=HDRTI(x,y,t)+b,  (1), wherein E(m, n) denotes optical energy measured at pixel (m, n) on the high-sensitivity CMOS camera (211), I(x, y, t) denotes an original dynamic scene, and b is noise, in which T is a time encoding operator determined by a mapping relationship between the polarization and time, R is a scene replication operator generated by the micro-lens array (207), D is an optical distortion operator generated by a spatial position difference among sixteen sub-lenses in the micro-lens array (207), and H is a circular convolution operator generated by polarization bandwidth of the linear polarizer array (210); and in order to restore the original dynamic scene, an inverse problem of formula (1) needs to be solved, that is, the iterative Tikhonov regularization is used to solve the problem by optimizing the following objective function, the objective function is expressed as follows:, arg
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     ), wherein Is is a threshold limit constant, ∥•∥2 denotes I2 norm, α is a regularization parameter, and Λ(I) denotes the Tikhonov regularization; in the process of image reconstruction, a two-dimensional image represented by E(m, n) acquired by the data acquisition system is first segmented into sixteen sub-images with equal size, and then optical distortion in each frame is calibrated by an image features recognition and matching algorithm; and in the iterative optimization process, an L-curve method is used to find the regularization parameter a, and the specific iterative steps are as follows:

(H*H+αΛ)I(k)=H*I+αI(k-1), and  (3), after k times of iterative optimization, an iterative optimization result I(k) is obtained, and finally, information without spatiotemporal aliasing is obtained by using an intensity threshold limit Is, the original dynamic scene Î(x, y, td) is obtained, td∈16.