Research On Image Preprocessing Algorithm Of Photoelectric System And Implementation On FPGA

Due to the influence of several factors such as the imaging environment,the properties of electronic components and sensor materials,real-time photoelectric video images are usually affected by severe noise pollution and blurry outlines.In order to reduce image mixed noise,sharpen image edges,and fulfill real-time requirements,an FPGA-based photoelectric image capture and preprocessing system is constructed by researching and developing preprocessing algorithms.The concrete research contents are as follows:(1)Aiming at the problems of single denoising of traditional filtering algorithms and low precision of edge detection algorithms,an improved image preprocessing algorithm is proposed:In terms of filtering,a modified alpha mean filtering method is used,which can effectively suppress mixed noise and improve the singleness of classic filtering algorithms for denoising.It is based on traditional median filtering and mean filtering;In terms of edge detection,a morphological edge identification approach is used,which can better extract and refine the image edge using the classic Sobel operator in combination with the morphological erosion and expansion technique.The improved algorithm is verified by the MATLAB platform,and the experimental results demonstrate that it outperforms the traditional technique in denoising and edge identification.(2)Build a system for capturing video images in real time.An image acquisition module,a data storage module,and an image display module are all part of the system.The image acquisition module chooses a CMOS camera to capture real-time images;the data storage module chooses SDRAM chips for data caching and calls the SDRAM controller IP core for related control;and the image display module calls the video output IP core to achieve VGA timing and completes the real-time display of the image after preprocessing.(3)Improve the image preprocessing algorithm’s design and port it to the FPGA platform.The modified alpha mean filter,for example,consists mostly of sub-modules like boundary point filling,window generation,complete comparison sorting,and addition tree summation,whereas morphological edge detection consists primarily of sub-modules like gradient computation,erosion,and expansion.To realize photoelectric image acquisition and preprocessing,the developed image preprocessing method is integrated to the real-time video image acquisition system.After the system is completed,verify the system acquisition results.Compile and synthesize each module,layer by layer superimpose the algorithm,and test the results.The experimental results show that the system proposed in this study efficiently suppresses noise and refines the image’s edge,increases the peak signal-to-noise ratio of the processed image by 2.42dB,and processes each image frame in roughly 0.033s.The processing impact of the system in this work is good and real-time,and it has a particular reference value in real-time image processing,according to a systematic examination.