| Project/Area Number |
60460127
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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 |
WATANABE Koji (1986) Faculty of Engineering, 工学部, 助手 (00107541)
宮川 洋 (1985) 東京大学, 工学部, 教授
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| Co-Investigator(Kenkyū-buntansha) |
HARASHIMA Hiroshi Faculty of Engineering, 工学部, 助教授 (60011201)
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| Project Period (FY) |
1985 – 1986
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| Project Status |
Completed (Fiscal Year 1986)
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| Budget Amount *help |
¥7,800,000 (Direct Cost: ¥7,800,000)
Fiscal Year 1986: ¥1,300,000 (Direct Cost: ¥1,300,000)
Fiscal Year 1985: ¥6,500,000 (Direct Cost: ¥6,500,000)
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| Keywords | Image Coding / Sampling Theorem / Vector Quantization / 動き補償符号化 |
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| Research Abstract |
The Object of the Project
Recently, digital transmittion and accumulation of image information have gained importance following the growth of the advanced information society. The authors have already proposed the sampling theorem of multidimensional signal which can be developed for processing and coding of images. This project have aimed the research of highly efficient image coding method applied to a low-bit-rate TV conference system and a still picture database.
The Results of the Project
(1)Image Coding Scheme with Motion Compensation and Motion Interpolation In this project, a new low-bit-rate video coding algorithm which is named Image Coding Method with Motion Compensation and Motion Interpolation is proposed.
It is necessary for the low-bit-rate video coding system to reduce information by skipping frames and to interpolate the skipped frames. The conventional systems interpolate them at the decoder, then the quality of the reconstructed images is not sufficient. In this method, the skipped frames are interpolated at the encoder by using the displacement vector of the transmitted frames and transmit the error signal between the interpolated image signal and source signal. It has been shown that this scheme improves the quality of the decoded images compared to the conventional method.
(2)Vector Quantization Using Interpolation for Picture Signals
A new image coding scheme named Vector Quantization Using Interpolation is proposed. This method vector-quantizes the error signal between the original image and interpolated image made from sab-sampled image. It has been shown that the deterioration of the performance of the vector quantizer for images outside of the training data can be greatly reduced.
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