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The k-means clustering algorithm is a commonly used algorithm for palette design. If an adequate initial palette is selected, a good quality reconstructed image of a compressed colour image can be achieved. The major problem is that a great deal of computational cost is consumed. To accelerate the k-means clustering algorithm, two test conditions are employed in the proposed algorithm. From the experimental results, it is found that the proposed algorithm significantly cuts down the computational cost of the k-means clustering algorithm without incurring any extra distortion. [ABSTRACT FROM AUTHOR]

This paper presents a data-hiding scheme, which hides the secret data in VQ compressed images using multiple codebooks. The secret data are hidden in the codebook indices after the VQ image compression is completed. The secret data can be extracted from the codebook indices when the decoding of the compressed image is performed. According to the experimental results, the hiding capacity and image quality outperform Jo and Kim's scheme. In other words, the proposed scheme is proved to be capable of supporting high hiding capacity and good image quality. [ABSTRACT FROM AUTHOR]

A novel image compression scheme based on the side match vector quantization (SMVQ) scheme is proposed. The goal of this scheme is to improve the image quality of the SMVQ scheme while keeping a low bit rate. The required bit rate of this scheme is variable, and the bit rate can be control by the proposed adaptive bit rate encoding mechanism. Three techniques are applied in this scheme: the local skewness of the image, the adaptive irregular sampling and the modified side-match distortion measurement to satisfy the variant encoding requirements of the various image contents. The experimental results show that the derailment is suppressed and the image quality is approximated to VQ and enhanced ∼2 dB from SMVQ at the same bit rate. Furthermore, the proposed scheme supports the adaptive bit rate encoding approach, which enables it to solve the trade-off between the image quality and the encoding bit rate. [ABSTRACT FROM AUTHOR]

A new scheme that aims to cut down on the computational cost of the vector quantization (VQ) encoding procedure is proposed in this paper. In this scheme, the correlation between the codewords in the codebook is exploited and three test conditions are designed to filter out the impossible codewords in the codebook. The design of test conditions is based on the concept of integral projection. From the experimental results, it is shown that the new scheme outperforms all the other schemes proposed so far in speeding up the VQ encoding procedure. When the codebook of 1024 codewords is used in the proposed scheme, the execution time it consumes is less than 2 per cent of that needed by the full search algorithm. The average time reduction rate is approximately 97.7 per cent compared to the execution time for the full search algorithm. In other words, the proposed scheme indeed provides an effective approach to speed up the VQ encoding procedure. [ABSTRACT FROM AUTHOR]