Design Of Image Acquisition And Processing System Based On FPGA Embedded Improved Algorithm

With the development of visual market in China,there is a growing demand for intelligent and fast industrial cameras.Because this kind of camera needs to work normally in the foggy and dark environment,it is necessary to solve the problem of poor image quality in the bad environment.n the environment with haze,because the small particles in the atmosphere have the function of absorbing and scattering light,the captured scene becomes dim,fuzzy and the contrast decreases,which will seriously affect the image performance,so it is very necessary to improve the image quality through image defogging and optimized algorithm.In this paper,the image acquisition and processing algorithm is developed by vivado suite,and the algorithm is modeled and simulated by MATLAB and Modelsim.Finally,FPGA is used as the hardware platform to realize the system functions.First of all,this paper summarizes the research background and significance of image acquisition and processing,and expounds the necessity of optimizing the collected image.At the same time,it introduces the basic concept of digital image and the method of image quality evaluation,so as to evaluate the image objective and subjective.In addition,through the analysis of the factors affecting the quality of the collected image,the attenuation model of the fog weather image is established based on the absorption and scattering characteristics of the atmospheric particles.Secondly,this paper compares the results of several common image acquisition and processing algorithms,evaluates the shortcomings of these algorithms through the image evaluation system,and optimizes the image.The results show that the CLAHE interpolation algorithm based on the dark channel prior has the best effect on video defogging,and meets the real-time function.The results show that the information entropy of the image is increased by 15%,the average gradient of the image is increased by 350%,and the mean square deviation of the image is increased by 119%,which shows that the clarity of the image is improved greatly.In addition,the processing efficiency of this system is improved by 30% compared with common CLAHE algorithm.At last,the hardware of the image acquisition and processing system based on FPGA is developed and simulated.The overall architecture of the system and the interface signals and implementation of each module are given.The results show that in the normal playback mode,using the global atmospheric light a and transmissivity t(x)of the previous image,the corresponding dark channel processing of this image can improve the Efficiency of calculation by 25%.In addition,using three RAM to store data in interpolation can not only prevent image pixels from being disordered,but also improve the efficiency of interpolation by 32%.At the same time,using the weight factor to weight the gray scale processed by the CLAHE and stretch algorithm.the mean square deviation of the image is increased by 10%,the mean gradient is increased by 215%,and the mean square deviation of the image is increased by 80%.Finally,the system can be multi-functional switched through the upper computer to slow play mode.