The Research On Image Compression Sensing Algorithm Based On FPGA

As the global population aging speed accelerating,the one-child faces the burden of raising the old man alone,and due to the fast pace of life and work pressure,the old man nursing robot such as monitoring system because of its real-time remote monitoring,abnormal alarm,intelligent navigation,location advantages becomes particularly important.However,because of the large amount of image data,the traditional way of image transmission consumes too many time and resource,the image coding is complex and difficult,and the high quality demand of signal channel,signal strong reliability is needed,which limits its application.Compressed sensing theory breaks through the limitation on the digital signal processing of Nyquist-shannon sampling theorem,is capable of high-speed signal sampling at the same time in the process of collecting signal at low speed to compress data signals,and has been widely applied in many occasions.The article studies the compression and transmission of images based on the remote monitoring of the old man,which lays a foundation for the receiving end to know the behavior state of the old man in real time.The goal is to study the Compressed Sensing algorithm and its FPGA implementation.The image acquisition and compression are transmitted to the receiver,the receiver is used to decode and display,to reduce the load of image processing,and to improve the real-time and reliability of the monitoring system,is conducive to timely discover and deal with emergency situation.According to the theoretical basis and actual needs of the project,the article studies three key problems of the compressed sensing algorithm,and applies the compressed sensing algorithm to the two-dimensional natural image.The selection of the sparse base,the selection of the observation matrix and the two methods of signal reconstruction are designed in detail.MATLAB simulation experiments are carried out to analyze the effect and influence of different reconstruction algorithms on image compression and recovery,laying the groundwork for selecting the best algorithm on subsequent hardware platform.This algorithm is applied to the field of image,combined with high performance Xilinx FPGA chip for collecting and parallel data transmission,and realizing VGA display on the FPGA hardware platform.The relevant research contents are as follows:1)This article introduces the background and significance of the theory of compressed sensing,and understands the application of the theory,and compares it with the traditional signal sampling processing,and discusses its advantages and the development status at home and abroad.2)The basic principle,algorithm design method and FPGA hardware basis of compressed sensing theory are discussed in detail.The structure features of different sparse bases and several common measurement matrix bases are introduced successively,and several reconstruction algorithms are analyzed and compared,among which the concrete reality of orthogonal matching tracing method and smooth l0 norm algorithm is emphatically studied.In this process,an algorithm is built to implement the hardware platform.3)the two reconstruction algorithms of compressive sensing theory are implemented in MATLAB and C languages,and the correctness and accuracy of the algorithm are verified by the recovery degree of the image and the intercepted data.Finally,the Verilog HDL language is used to design the FPGA hardware system,and the CS algorithm is embedded in the system on the chip system to realize the reconstruction process.Therefore,the result is proved to be better and the original image is restored.The hardware system designed in this article realizes the image compression sensing algorithm,which lays a foundation for the image transmission of the guardian system,and is of great significance for promoting the application and development of intelligent monitoring system.