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1

Improved vector quantization scheme for grayscale image compression

Hu Y. C., Chen W. L., Lo C. C., Chuang J. C.

Opto-Electronics Review

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2012

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Vol. 20, No. 2

187-193

EN

This paper proposes an improved image coding scheme based on vector quantization. It is well known that the image quality of a VQ-compressed image is poor when a small-sized codebook is used. In order to solve this problem, the mean value of the image block is taken as an alternative block encoding rule to improve the image quality in the proposed scheme. To cut down the storage cost of compressed codes, a two-stage lossless coding approach including the linear prediction technique and the Huffman coding technique is employed in the proposed scheme. The results show that the proposed scheme achieves better image qualities than vector quantization while keeping low bit rates.

2

Efficient greyscale image compression technique based on vector quantization

Hu Y. C., Chuang J. C., Lo C. C., Li C. Y.

Opto-Electronics Review

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2011

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Vol. 19, No. 1

104-113

EN

In this paper, a novel greyscale image coding technique based on vector quantization (VQ) is proposed. In VQ, the reconstructed image quality is restricted by the codebook used in the image encoding/decoding procedures. To provide a better image quality using a fixed-sized codebook, the codebook expansion technique is introduced in the proposed technique. In addition, the block prediction technique and the relatively address technique are employed to cut down the required storage cost of the compressed codes. From the results, it is shown that the proposed technique adaptively provides better image quality at low bit rates than VQ.

3

A Fast VQ Codebook Generation Algorithm Based on Otsu Histogram Threshold

Huang C-C., Tsai D-S., Horng G.

Fundamenta Informaticae

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2009

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Vol. 91, nr 3-4

563-579

EN

In vector quantization, the codebook generation problem can be formulated as a classification problem of dividing N_p training vectors into N_c clusters, where N_p is the training size of input vectors and N_c is the codeword size of codebook. For large Np and Nc, a traditional search algorithmsuch as the LBG method can hardly find the global optimal classification and needs a great deal of calculation. In this paper, a novel VQ codebook generation method based on Otsu histogram threshold is proposed. The computational complexity of squared Euclidean distance can be reduced to O(N_p log_2 N_c) for a codebook with gray levels. Our method provides better image quality than recent proposed schemes in high compression ratio. The experimental results and the comparisons show that this method can not only reduce the computational complexity of squared Euclidean distance but also find better codewords to improve the quality of the resulted VQ codebook.

4

Fast VQ Codebook Generation Method Using Codeword Stability Check and Finite State Concept

Tsai P., Hu Y-C., Yeh H-L.

Fundamenta Informaticae

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2008

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Vol. 87, nr 3-4

447-463

EN

The codebook design in the vector quantization scheme is important because it affects the image quality of the encoded image. The Linde-Buzo-Gray (LBG) codebook generation algorithm is well known and a popular choice among codebook users. However, a heavy computational complexity is consumed for the iteratively clustering process in the LBG algorithm. In this paper, the similarity of codewords in consecutive rounds of the LBG algorithm is exploited to reduce the computational complexity. By checking the stability of codewords, the status of each codeword in the codebook can be determined. Only the unstable codewords are refined to generate the new codebook. The proposed method can be further improved by cooperating with the finite state technique. Experimental results show that the computational complexity of the proposed method is reduced to about 4% of the LBG algorithm while achieving a slightly worse image quality.

5

A Refined VQ-Based Image Compression Method

Chan Y-K, Wang H-F., Lee C-F.

Fundamenta Informaticae

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2004

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Vol. 61, nr 3,4

213-221

EN

This paper presents a refined VQ-based image compression method which modifies the traditional VQ-based image compression method. The refined VQ-based image compression method further lossless encodes the compression data which is generated by the traditional VQ-based image compression method into a set of compression codes. The index image generated by the refined method is a contracted image of the compressed image, which can be used as the preview of the compressed image on image management. Although the PSNRs of the reconstructed images that are decoded by the refined VQ-based image compression method and the traditional VQ-based image compression method are the same, the refined VQ-based image compression method provides a better storage efficiency.