BFA based neural network for image compression
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A novel Bacterial Foraging Algorithm (BFA) based neural network is presented for image compression. To improve the quality of the decompressed images, the concepts of reproduction, elimination and dispersal in BFA are firstly introduced into neural network in the proposed algorithm. Extensive experiments are conducted on standard testing images and the results show that the proposed method can improve the quality of the reconstructed images significantly.
Key wordsBacterial Foraging Algorithm (BFA) Artificial Neural Network (ANN) Back Propagation (BP) Image compression
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- I. Vilovic. An experience in image compression using neural networks. 48th International Symposium ELMAR-2006 on Multimedia Signal Processing and Communications, Zadar, Croatia, June 7–9, 2006, 95–98.Google Scholar
- N. Sonehara, M. Kawato, S. Miyake, et al. Image data compression using a neural network model. Proceedings of IEEE International Joint Conference on Neural Networks, Washington DC, USA, June 18–22, 1989, 35–41.Google Scholar
- J. H. Zheng. BP neural network for image data compression. Computer Simulation, 18(2001)2, 33–36 (in Chinese). 郑建华. 图象数据压缩的 BP 神经网络方法研究. 计算机仿真, 18(2001)2, 33–36.Google Scholar
- G. Qiu, T. J. Terrell, and M. R. Varley. Improved image compression using backpropagation networks. Workshop on Neural Network Applications and Tools, Liverpool, UK, September 13–14, 1993, 73–81.Google Scholar
- S. F. Wang and G. L. Li. Application of a BP neural network based on genetic algorithm in image compression. Chinese Journal of Quantum Electronics, 24 (2007)4, 425–428 (in Chinese). 王世芳, 李国丽. 基于遗传算法的 BP 神经网络在图像压缩中的应用. 量子电子学报, 24(2007)4, 425–428.Google Scholar
- W. J. Tang, Q. H. Wu, and J. R. Saunders. Bacterial foraging algorithm for dynamic environments. 2006 IEEE Congress on Evolutionary Computation, Vancouver, Canada, July 16–21, 2006, 4467–4473.Google Scholar