JOURNAL ARTICLE

<title>Image coding based on two-channel conjugate vector quantization</title>

Jae Yeal NamK.R. Rao

Year: 1991 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 1452 Pages: 485-496   Publisher: SPIE

Abstract

Two channel conjugate VQ (TCCVQ) has been recently proposed for speech coding. Compared to the ordinary VQ, two channel conjugate VQ requires less computational complexity, less storage (memory) requirement and is more robust against channel errors [8], [16], [17]. This technique is now extended to image coding. Initial investigation confirms these advantages of two channel conjugate VQ. For noise free channel the performances of both techniques are similar. However, when channel noise is injected, for the same bit rate, images reconstructed based on two channel conjugate VQ are subjectively more pleasing (less visible distortion) compared to those based on ordinary VQ. Both VQ techniques are also applied to a well known separating mean VQ (SMVQ) [2], [20] and are tested for robustness against channel errors. Computer simulations demonstrate the success of the two channel conjugate VQ technique for image data compression at various bit rates.

Keywords:
Vector quantization Conjugate Codebook Channel (broadcasting) Coding (social sciences) Mathematics Algorithm Speech recognition Robustness (evolution) Computer science Decoding methods Artificial intelligence Pattern recognition (psychology) Telecommunications Statistics Biology

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Topics

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

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