Embedded Image Compression Algorithm and FPGA Implementation Based on BP Neural Networks

Abstract:

At present, because more embedded image compressions are single, various compression methods have not transplant to embedded equipment. In this paper, A BP neural network based image compression methods have been proposed. The neural network is trained more and more, and obtained a set of weights and thresholds usefully. Then, use the FPGA to achieve, In the FPGA, using the framework of soft-core Nios Ⅱ way. Ultimately, compression program written using Verilog and burned into the FPGA. Experiments show that the system has the advantages of high compression ratio, small size, and can stable operation.

• Periodical: Applied Mechanics and Materials (Volume 65)
• Pages: 415-418
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.65.415
• Online since: June 2011
• Authors: Guang Ming Li, Zhen Qi He
• Keywords: BP Neural Network (BPNN), Image Compression, Verilog Language

References

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