2023 Fiscal Year Final Research Report
Development of a lossless gradation compression technique by retinal information processing
| Project/Area Number |
21K12052
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 61040:Soft computing-related
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| Research Institution | Chukyo University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
大竹 敢 玉川大学, 工学部, 教授 (20296883)
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Keywords | 可逆階調圧縮 / 時空間分割 |
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| Outline of Final Research Achievements |
In this research project, we have developed a method to decompose input data into binary data sequences and integrate them using a multistage digital integrator, thereby restoring the input data without degradation. In our method, two-stage SD-CNN, a mimic of converting external image information into biological pulses in the retina of a living body, is employed. We have also realized a highly accurate bit-depth expansion technique that efficiently reconstructs a visually lossless quality image from a low-gradation image.
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| Free Research Field |
知能情報処理
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| Academic Significance and Societal Importance of the Research Achievements |
学術的意義として，生体の網膜における情報処理を応用することで，画像を含む様々なデータを可逆復元できることを明らかにした点が挙げられる．また，階調圧縮のみならず，海中など狭帯域の通信環境に適合するデータ伝送方式への応用が可能である点に社会的意義がある．
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