Research On Intelligent Computing Optical Imaging System

With the development of optical imaging technology,the method of improving the imaging performance of optical systems by increasing the number of lenses has made the design of lenses and systems more and more complicated.For complex multi-optical axis optical systems that are required by the working environment and working nature,if the complexity of the optical system structure is still increased to improve the quality of imaging,the reliability and shock resistance of the system will be severely challenged.In order to simplify the structure and cost of the optical system,this paper combines digital image processing technology with image restoration to repair image blur caused by aberrations.Due to the spatial variation characteristics of the point spread function of the actual optical system,the image restoration effect based on the space-invariant point spread function is not very good.Therefore,this paper uses a spatially varying point spread function to recover the image.There are two methods for obtaining the point spread function of spatial variation.One is to use the optical software CODEV to simulate the actual optical system to generate a spatially varying point spread function;the other is to measure the indirect measurement by an optical function measuring instrument and pass the calculation.The statistics of the real image show that the super Laplace model can fit the edge distribution of the heavy tail characteristic more accurately,So that the result of the restoration is closer to the original clear image.In this paper,Matlab simulation is used to verify the effectiveness of the super Laplacian priori non-blind deconvolution algorithm for image restoration.Two image quality evaluation indicators PSNR and SSIM are used to objectively evaluate the impact of the restoration with the three changed regularization parameters ? ?? ??.According to the experimental results,the three parameters ? ?? ?? are respectively selected 0.6?600 and 3000 as the initialization values when the DSP implements the algorithm.The algorithm is finally implemented on the hardware platform of FPGA+DSP.The FPGA completes the image preprocessing,and the DSP completes the restoration of the blurred image.The spatially varying point spread function used by the DSP to reconstruct an image is obtained by experimental measurements.The experimental platform with computational optical imaging system as the core is built.The experimental results show that the computational optical imaging system has good restoration effect on the blurred image affected by single lens aberration,and its image quality is improved,and lightweight of the optical imaging system is realized.