Research On Image Processing Algorithm Based On Morphology And Logarithm Theory And Its FPGA Implementation

In recent years,multimedia technology has developed rapidly,and humans are increasingly using images to communicate information in social life.Therefore,digital image processing technology is particularly important.At present,digital image processing technology is widely used in the field of medical,military,security and remote sensing.However,with the increase of the resolution of digital images and the number of images to be processed,real-time image processing requires higher and higher processing speeds.Therefore,the design of digital image processing systems which have both accuracy and efficiency has become more and more important,the traditional software-based digital image processing system can no longer meet the needs.FPGA has the characteristics of parallel execution and high-speed calculation.It also contains a lot of logic resources.FPGA can be well applied to the design of image processing system.Many studies have shown that FPGA-based image processing systems can significantly improve the execution speed of algorithms and meet the requirements of real-time image processing.This article focuses on the design and implementation of digital image processing algorithms on FPGA.The FPGA chip uses Xilinx's Zynq-7000 series Zedboard development board,Verilog HDL is used to write the hardware implementation logic of the image processing algorithm.The module is simulated on the Modelsim software.The step of comprehensive optimization and layout through is achieved on the Vivado development tools.Finally,the program is download to FPGA chips for power-on debugging.1.In this paper,an adaptive morphological processing algorithm for grayscale images is designed and implemented on FPGA.Traditional gray morphology operators use fixed structural elements to process the entire image,which will lose the detailed information of the image.The adaptive gray morphology operators can automatically adjust the shape and size of the structural elements based on the local information of the image so that the image processing effect is better.Firstly,this paper implements adaptive gray morphology operator on MATLAB software,and compares the processing effect with traditional gray morphology operator to verify the superiority of adaptive gray morphology operator.Then,the adaptive gray morphology operator is designed and implemented on FPGA to complete the adaptive gray morphology processing system which including image storage module,square window generation module,structural element selection module,dilate operation module,erosion operation module,open operation module,closed operation module and image display module.The function of the designed system is verified through simulation and debugging.Finally,the running time of the adaptive gray morphology processing algorithm on MATLAB software and FPGA hardware is compared,which proves that the FPGA-based adaptive gray morphology processing system can significantly improve the processing speed of the algorithm.2.In this paper,an image edge detection algorithm based on a logarithmic image processing model is designed and implemented on FPGA.The logarithmic image processing model can effectively solve the problem that the pixels' addition and subtraction operations will exceed the image gray interval in the linear image processing.Firstly,the image edge detection algorithm based on the logarithmic image processing model and the traditional Sobel edge detection algorithm are implemented in the MATLAB software.The effect of edge detection is compared to verify that the edge detection algorithm based on the logarithmic image processing model can more accurately detect the edge of the image.Then designed the image edge detection system based on the logarithmic image processing model on FPGA.The logarithmic image processing module was implemented using the cordic algorithm,and it was combined with the edge detection module,image storage module,square window generation module,and image display module to form the entire edge detection system.By comparing the processing effect and running time of the algorithm on MATLAB software and FPGA hardware,it is proved that the edge detection system can effectively detect the edges of the image and improve the processing speed of the image.