High-performance video integrated coding using high-order variable lifting structure
| Project/Area Number |
16K18100
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Communication/Network engineering
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| Research Institution | University of Tsukuba |
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Principal Investigator |
Suzuki Taizo 筑波大学, システム情報系, 准教授 (30615498)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | リフティング / フレーム間予測 / 適応変換 / 高速変換 / 多次元変換 / 符号化標準規格 / 離散X変換 / 映像符号化 / 画像符号化 / 高次可変リフティング構造 / 類似フレーム間予測 / 差分信号適応変換 |
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| Outline of Final Research Achievements |
To put into practical use new "similar inter-frame prediction" and "differential signal adaptive conversion" for high-performance video integrated coding corresponding to various high-performance video, such as free-point view video, free-focus view video, high dynamic range video, hyperspectral video, we proposed many transforms that can be a low-complexity and high-efficiency basic technology. On the other hand, we researched on the security of coding. As a result, we presented six journal articles and 23 conference presentations in and outside of Japan.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では，今後普及が進むであろう高機能映像を効率良く処理するために欠かせない技術として，低演算かつ高効率な変換および高セキュア符号化技術に関する成果を上げた．しかし今回は応用として高機能映像を取り上げたが，本研究における成果は益々発展する人工知能（AI）技術やIoT社会においての基盤技術となり得るものばかりである．これら基盤技術を元に，今後の当該分野の発展が更に期待される．
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Report
(4 results)
Research Products
(27 results)
