JOURNAL ARTICLE

<title>Index-compressed residual adaptive vector quantization</title>

Jamshid ShanbehzadehPhilip OgunbonaAbdolhosain SarafzadehSayyad Najafi

Year: 1998 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3387 Pages: 78-86   Publisher: SPIE

Abstract

This paper introduces a new scheme for still image compression based on Vector Quantization (VQ). The new scheme first vector quantized the image, then the indices obtained from quantization are compressed and transmitted. The indices are used as a classifier to identify the active areas of the image. The residual of active areas are vector quantized in the second step and the indices generated are transmitted. The advantage of new scheme is to present the active areas of the coded image accurately without overhead requirement. This scheme shows better subjective and objective in comparison with similar VQ schemes.

Keywords:
Vector quantization Residual Quantization (signal processing) Artificial intelligence Computer science Linde–Buzo–Gray algorithm Computer vision Learning vector quantization Pattern recognition (psychology) Algorithm Mathematics

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Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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