A wavelet-VQ system for real-time video compression |
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Authors: | Agustin Ramirez-Agundis Rafael Gadea-Girones Ricardo Colom-Palero Javier Diaz-Carmona |
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Affiliation: | (1) Department of Electronic Engineering, Instituto Tecnológico de Celaya, Av. Tecnologico s/n, 38010 Celaya, Gto., Mexico;(2) Department of Electronic Engineering, Universidad Politecnica de Valencia, Camino de Vera s/n, 46020 Valencia, Spain |
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Abstract: | This paper presents a scheme and its Field Programmable Gate Array (FPGA) implementation for a system based on combining the
bi-dimensional discrete wavelet transformation (2D-DWT) and vector quantization (VQ) for image compression. The 2D-DWT works
in a non-separable fashion using a parallel filter structure with distributed control to compute two resolution levels. The
wavelet coefficients of the higher frequency sub-bands are vector quantized using multi-resolution codebook and those of the
lower frequency sub-band at level two are scalar quantized and entropy encoded. VQ is carried out by self organizing feature
map (SOFM) neural nets working at the recall phase. Codebooks are quickly generated off-line using the same nets functioning
at the training phase. The complete system, including the 2D-DWT, the multi-resolution codebook VQ, and the statistical encoder,
was implemented on a Xilinx Virtex 4 FPGA and is capable of performing real-time compression for digital video when dealing
with grayscale 512 × 512 pixels images. It offers high compression quality (PSNR values around 35 dB) and acceptable compression
rate values (0.62 bpp).
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Keywords: | Wavelet transform Vector quantization Real-time image compression Self-organizing feature map |
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