등록
[6GV] 확률 추정 기반 영상 압축 방법 및 장치
- 발명자
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이주영, 조승현, 백승권, 석진욱, 정세윤, 임웅, 김연희, 김종호, 고현석, 김휘용, 최진수
- 출원번호
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16585658 (2019.09.27)
- 공개번호
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20200107023 (2020.04.02)
- 등록번호
- 11412225 (2022.08.09)
- 출원국
- 미국
- 협약과제
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18HR2300, [통합과제] 초실감 테라미디어를 위한 AV부호화 및 LF미디어 원천기술 개발,
최진수
- 초록
- Disclosed herein is a context-adaptive entropy model for end-to-end optimized image compression. The entropy model exploits two types of contexts. The two types of contexts are a bit-consuming context and a bit-free context, respectively, and these contexts are classified depending on the corresponding context requires the allocation of additional bits. Based on these contexts, the entropy model may more accurately estimate the distribution of each latent representation using a more generalized form of entropy models, thus improving compression performance.
- KSP 제안 키워드
- Compression performance, End to End(E2E), Entropy model, Image Compression, Image processing, context adaptive