1987 Fiscal Year Final Research Report Summary
High Efficient Image Coding System Using Vector Quantization in Transform Domain
| Project/Area Number |
61460129
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| Research Category |
Grant-in-Aid for General Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
電子通信系統工学
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| Research Institution | The University of Tokyo |
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Principal Investigator |
HARASHIMA Hiroshi Faculty of Engineering, The University of Toky, 工学部, 助教授 (60011201)
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| Co-Investigator(Kenkyū-buntansha) |
WATANABE Kouji Faculty of Engineering, The University of Tokyo, 工学部, 助手 (00107541)
SAITO Takahiro Faculty of Engineering, Kanagawa University (BABA,Hiroshi), 工学部, 助教授 (10150749)
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| Project Period (FY) |
1986 – 1987
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| Keywords | IMAGE CODING / VECTOR QUANTIZATION / DISCRETE COSINE TRANSFORM CODING WITH VECTOR QUANTIZATION / dct-vq / differential vector quantization / 差分変換ベクトル量子化 / 直交変換領域高速探索方式 |
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| Research Abstract |
In this project, image coding schemes using vector quantization are systematically studied. The results of this research are as follows.
(1)Consideration concerning Vector Quantization fo Picture Signals
Two problems are pointed out in application of vector quantization. One is the complexity of vector quantizer and the other is robustness of vector quantizer performance.
(2)Discrete Cosine Transform Coding with Vector Quantization (DCT-VQ)
A new vector quantization scheme using discrete cosine transform, named DCT-VQ is proposed. To arrive at an universal vector quantizer, vector quantizers are designed for a standard probability distribution independent of picture signals. The complexity is greatly reduced because of a decomposition of transform domain into vectors.
(3)Adaptive DCT-VQ
Adaptive DCT-VQ is presented, which employs adaptive control of coding parameters according to the local property of picture signals in order to improve the performance of DCT-VQ. The simulations have shown that the adaptive DCT-VQ outperforms the conventional adaptive transform codings. An application of this scheme to color image coder using color coordinate conversion is also presented.
(4)Differential Vector Quantization
To realize robust quantization, differential vector quantization is also proposed, which vector-quantizes predictive error signals using universal vector quantizer designed for standard distribution.
(5)Fast Search Algorithms for Vector Quantization in orthogonal Transform Domain
In order to attain fast search at vector quantization, a partial distance algorithm and nearest-neighbor search algorithm are proposed, both in the orthogonal transform domain. These algorithms needs less multiplications than the tree-search algorithms for signal sources such as picture signals which have concentration in the transform domain power distribution.
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