Bhuiyan, I.H., Hasan, M.K., Haque, M.A. and Nait-Charif, H., 2001. A robust method for image compression using dynamically constructive neural network. In: Signal Processing and its Applications: Sixth International Symposium, 13-16 August 2001, Kuala Lumpur, Malaysia, pp. 525-528.
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A dynamically constructive neural network (DCNN) is proposed for still image compression. The main feature of the proposed dynamical construction is its robustness to input-to-hidden and hidden-to-output link failure. A wavelet transform based sub-image block classification technique is also proposed for partitioning training images into image clusters. Each cluster is used as a training set for training a particular DCNN. This ensures the generalization capability of DCNNs. Computer simulation results demonstrate superiority of the proposed scheme in terms of peak signal to noise ratio and robustness as compared to that of other recent methods
|Item Type:||Conference or Workshop Item (Paper)|
|Additional Information:||International Symposium on Signal Processing and Its Applications, 13-16 August, 2001, Shangri-La Hotel, Kuala Lumpur, Malaysia. Vol 2|
|Subjects:||Arts > Graphic Arts|
Generalities > Computer Science and Informatics
|Deposited By:||Ms MJ Bowden|
|Deposited On:||02 Jan 2008|
|Last Modified:||07 Mar 2013 14:41|
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