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Design and Implementation of the FPGA Image Reconstruction System Based on Compressed Sensing

Author: WangXing
Tutor: MaXueWen
School: Northeastern University
Course: Circuits and Systems
Keywords: Compressed Sensing Image Reconstruction SOPC Nios Ⅱ FPGA
CLC: TP391.41
Type: Master's thesis
Year: 2013
Downloads: 8
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Abstract


Compressed sensing theory for the sparse signal, which is sampled at the same time to complete data compression, thus saving a lot of computing resources, storage resources and transfer resources, therefore, the compressed sensing theory in signal processing field has prominent advantages and broad application prospects. Compressed sensing theory mainly includes three parts:signal sparse transformation, the design of the observation matrix and the signal reconstruction. This study will focus on the most important problem on signal reconstruction. Since the compressed sensing theory, especially the reconstruction of signal is facing a large amount of data operations, and the image as a two-dimensional signal, which involves the reconstruction algorithm computation will be more substantial. The FPGA will be introduced in the image reconstruction algorithm, using its powerful parallel computing ability can effectively solve the problem of large amounts of data operations.This article is based on the theory of compressed sensing of image reconstruction system, designed and completed on the ALTERA DE2platform. System using a Cyclone Ⅱ series EP2C35FPGA, the whole system was designed with collaborative software and hardware implementations. Hardware aspects:on the basis of the analysis of the system requirements, through the design of each hardware module of the system, complete the custom of NIOS Ⅱ processor. System mainly includes image reconstruction module, image display module. Software aspects:on the PC using MATLAB to simulate sparse transform method and image reconstruction algorithm to evaluate the performance of the algorithm, through the contrastive analysis of image reconstruction algorithm, determine the DWT algorithm and OMP algorithm is used to implement image reconstruction. The NIOS Ⅱ IDE environment using C language programming and debugging of the algorithm, finally analyzing the whole system resources and evaluating the effect of image reconstruction.Through collaborative debugging of hardware modules and software program to reach the image reconstruction system expected effects.The testing results show that the image reconstruction system, realized on the DE2 development platform, can effectively realize the image reconstruction. For the OMP algorithm complex iterative parts, using a matrix multiplier, which is realized by using VHDL hardware language operation, greatly improve the efficiency of image reconstruction.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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