Interpolative Adaptive Vector Quantization

H. Sun; C, N. Manikopoulos

doi:10.1117/12.947050

18 July 1988 Interpolative Adaptive Vector Quantization

H. Sun, C, N. Manikopoulos

Proceedings Volume 0939, Hybrid Image and Signal Processing; (1988) https://doi.org/10.1117/12.947050
Event: 1988 Technical Symposium on Optics, Electro-Optics, and Sensors, 1988, Orlando, FL, United States

Abstract

Adaptive vector quantization with interpolation has been applied to the problem of edge degradation. An activity index A has been devised and used to classify the image into active and non-active regions according to the level of local detail. The non-active blocks were encoded by sampling and decoded by interpolation. Each active block was split into four smaller blocks which were coded by vector quantization. The number of samples extracted from each non-active block equals the size of the small blocks. So, each non-active block can be quantized with the same codebook. Thus, only one codebook was required. This greatly reduces the encoding and decoding computational effort. Computer simulation experiments have been carried out with an image of 256x256 pixels, 8 bit quantization and of medium detail level. The rate distortion curves obtained have shown that the adaptive interpolative encoding scheme outperforms alternative non-adaptive coding methods. Moreever, the edge information in the reconstructed image is well preserved . This was achieved at coding bit rates in the range of 0.8 to 1.0 bits per pixel.

Citation Download Citation

H. Sun and C, N. Manikopoulos "Interpolative Adaptive Vector Quantization", Proc. SPIE 0939, Hybrid Image and Signal Processing, (18 July 1988); https://doi.org/10.1117/12.947050

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