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Deep Learning based x4 and x8 Super-Resolution for Cultural Property Images
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딥러닝 기반 문화재 영상에 대한 4배 및 8배 초해상화

논문 기본 정보

Type
Proceeding
Author
Chaeyeon Son (한국과학기술원) Soo Ye Kim (한국과학기술원) Juyoung Kim (한국전자통신연구원) Munchurl Kim (한국과학기술원)
Journal
The Korean Society Of Broad Engineers 한국방송미디어공학회 학술발표대회 논문집 한국방송·미디어공학회 2020 추계학술대회
Published
2020.11
Pages
118 - 122 (5page)

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Deep Learning based x4 and x8 Super-Resolution for Cultural Property Images
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문화재 영상 데이터는 방대한 양으로 인해 고해상도로 모두 저장이 어렵거나 시간이 지나 상대적으로 화질이 낮은 영상들이 다수 존재하기에 초해상화가 필요한 상황이 많다. 따라서 본 논문에서 처음으로 문화재 영상에 특화된 4 배 및 8 배 딥러닝 기반 초해상화 방식을 제안한다. 문화재 영상 데이터는 배경이 단조롭고 물체가 영상 중간에 위치한다는 특징이 있어 이를 고려해 중간 부분에서만 패치를 추출하는 방식을 적용하여 의미 있는 패치로 학습이 되도록 한다. 또 자연 영상 데이터 셋인 DIV2K 를 사용해 학습하는 방식과 직접 구성한 문화재 데이터 셋을 이용해 학습하는 방식, 그 둘을 적절히 함께 사용하여 학습하는 전이 학습 방법까지 세 가지로 학습하여 초해상화의 성능을 향상시키는 방법을 제안한다. 그 결과, 쌍삼차 보간법(Bicubic interpolation)보다 4 배 초해상화에서는 약 1.25dB, 8배 초해상화에서는 약 1.26dB의 성능 개선을 확인하였으며, 단순 DIV2K로 학습한 방식보다는 4배에서는 0.06dB, 8배에서는 0.17dB의 성능 개선을 확인하였다.

Contents

요약
1. 서론
2. 문화재 영상 데이터 셋 활용
3. 학습 방법
4. 실험결과
5. 결론
참고문헌

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