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Design of M-channel pseudo near perfect reconstruction QMF bank for image compression

Author(s): Anamika Jain | Aditya P. Goel

Journal: Signal & Image Processing
ISSN 2229-3922

Volume: 3;
Issue: 4;
Start page: 95;
Date: 2012;
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Keywords: Bits per pixel (bpp) | Embedded Zerotree Wavelet (EZW) | evolutionary Algorithm | Huffman Encoder | near perfect reconstruction | Peak signal to noise ratio (PSNR) | Pseudo QMF bank | Particle Swarm optimization(PSO) | reconstruction error (RE).

This paper proposes particle swarm optimization method to design M channel near perfect reconstructionpseudo QMF banks used in transforming stage of image coder. The filter bank is designed to have highest entropy based coder. To achieve high energy compaction and least distortion, design problem is formulated as a combination of the coding gain, low dc leakage conditions and stopband attenuation. For distortion free signal representation perfect reconstruction and good visual quality measures are imposed as constraints. The design problem is solved using (particle swarm optimization) PSO technique for minimizing filter tap weights. The technique find out solution by searching feasible solutions that achieve the best solution for the objectives criteria mentioned above. The performance of this optimization technique in filter bank design for image compression is evaluated in terms of both objective quality via coding gain, PSNR measures and subjective visual quality measure using both JPEG baseline image coder and an Embedded Zerotree Wavelet (EZW) coder. For comparison same test images for approximately same conditions and characteristics are used to measure compression ratio and peak signal to noise ratio (PSNR) for lower bit rates.
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