Abstract
A method of fuzzy optimization design based on neural networks is presented as a new method of image processing. The combination system adopts a new fuzzy neuron network (FNN) which can appropriately adjust input and output, and increase robustness, stability and working speed of the network. Besides FNN, wavelet transform also be applied to compression algorithm for a higher and controllable compression rate. As shown by experimental results, the communication system can compress and decompress image data dynamically which proves that it is a more practical and more effective method than traditional methods for communication in wireless networks, and it is especially better at video data transmitting.
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Su, J.L., Yimin, C., Ouyang, Z. (2007). An Image Compression Algorithm with Controllable Compression Rate. In: Cao, BY. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71441-5_10
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DOI: https://doi.org/10.1007/978-3-540-71441-5_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71440-8
Online ISBN: 978-3-540-71441-5
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