Still image compression method based on adaptive block segmentation vector quantization technique

T. Nakayama; K. Takeuchi; M. Konda; Koji Kotani; T. Ohmi

Still image compression method based on adaptive block segmentation vector quantization technique

T. Nakayama, K. Takeuchi, M. Konda, Koji Kotani, T. Ohmi

ENG - Electronic Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

In order to increase the performance of image compression by Vector Quantization (VQ), we have developed a new still image compression algorithm. Adaptive block segmentation vector quantization (ABS-VQ) method, which is composed of three key techniques, i.e., the resolution conversion, the quad tree data structure and the Mean-Residual VQ, can realize much superior compression performance than the worldwide standard JPEG and JPEG-2000. On the compression of the XGA (1024×768 pixels), SXGA (1280×1024 pixels) and UXGA (1600×1200 pixels) images including text, for instance, there exists the overwhelming performance superiority of more than 5 dB in compressed image quality.

Original language	English
Pages	275-278
Number of pages	4
Publication status	Published - 2003 Dec 17
Event	Proceedings: 2003 International Conference on Image Processing, ICIP-2003 - Barcelona, Spain Duration: 2003 Sep 14 → 2003 Sep 17

Other

Other	Proceedings: 2003 International Conference on Image Processing, ICIP-2003
Country	Spain
City	Barcelona
Period	03/9/14 → 03/9/17

ASJC Scopus subject areas

Hardware and Architecture
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

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title = "Still image compression method based on adaptive block segmentation vector quantization technique",

abstract = "In order to increase the performance of image compression by Vector Quantization (VQ), we have developed a new still image compression algorithm. Adaptive block segmentation vector quantization (ABS-VQ) method, which is composed of three key techniques, i.e., the resolution conversion, the quad tree data structure and the Mean-Residual VQ, can realize much superior compression performance than the worldwide standard JPEG and JPEG-2000. On the compression of the XGA (1024×768 pixels), SXGA (1280×1024 pixels) and UXGA (1600×1200 pixels) images including text, for instance, there exists the overwhelming performance superiority of more than 5 dB in compressed image quality.",

author = "T. Nakayama and K. Takeuchi and M. Konda and Koji Kotani and T. Ohmi",

year = "2003",

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note = "Proceedings: 2003 International Conference on Image Processing, ICIP-2003 ; Conference date: 14-09-2003 Through 17-09-2003",

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AU - Nakayama, T.

AU - Takeuchi, K.

AU - Konda, M.

AU - Kotani, Koji

AU - Ohmi, T.

PY - 2003/12/17

Y1 - 2003/12/17

N2 - In order to increase the performance of image compression by Vector Quantization (VQ), we have developed a new still image compression algorithm. Adaptive block segmentation vector quantization (ABS-VQ) method, which is composed of three key techniques, i.e., the resolution conversion, the quad tree data structure and the Mean-Residual VQ, can realize much superior compression performance than the worldwide standard JPEG and JPEG-2000. On the compression of the XGA (1024×768 pixels), SXGA (1280×1024 pixels) and UXGA (1600×1200 pixels) images including text, for instance, there exists the overwhelming performance superiority of more than 5 dB in compressed image quality.

AB - In order to increase the performance of image compression by Vector Quantization (VQ), we have developed a new still image compression algorithm. Adaptive block segmentation vector quantization (ABS-VQ) method, which is composed of three key techniques, i.e., the resolution conversion, the quad tree data structure and the Mean-Residual VQ, can realize much superior compression performance than the worldwide standard JPEG and JPEG-2000. On the compression of the XGA (1024×768 pixels), SXGA (1280×1024 pixels) and UXGA (1600×1200 pixels) images including text, for instance, there exists the overwhelming performance superiority of more than 5 dB in compressed image quality.

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T2 - Proceedings: 2003 International Conference on Image Processing, ICIP-2003

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