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Adaptive Wavelet Transform for Hologram Compression

홀로그램 압축을 위한 적응적 웨이블릿 변환

  • Received : 2021.01.12
  • Accepted : 2021.03.18
  • Published : 2021.03.30

Abstract

In this paper, we propose a method of compressing digital hologram standardized data provided by JPEG Pleno. In numerical reconstruction of digital holograms, the addition of random phases for visualization reduces speckle noise due to interference and doubles the compression efficiency of holograms. Holograms are composed of completely complex floating point data, and due to ultra-high resolution and speckle noise, it is essential to develop a compression technology tailored to the characteristics of the hologram. First, frequency characteristics of hologram data are analyzed using various wavelet filters to analyze energy concentration according to filter types. Second, we introduce the subband selection algorithm using energy concentration. Finally, the JPEG2000, SPIHT, H.264 results using the Daubechies 9/7 wavelet filter of JPEG2000 and the proposed method are used to compress and restore, and the efficiency is analyzed through quantitative quality evaluation compared to the compression rate.

본 논문에서는 JPEG Pleno에서 제공하는 디지털 홀로그램 표준화 데이터를 압축하는 방법을 제시한다. 디지털 홀로그램의 수치 복원에서 시각화를 위한 랜덤 위상의 추가는 간섭현상으로 인한 스페클 노이즈와 더블어 홀로그램의 압축 효율을 떨어트린다. 홀로그램은 완전 복소의 부동소수점 형태의 데이터로 구성되며 초고해상도와 스페클 노이즈로 인해 홀로그램 특성에 맞춘 압축기술 개발이 필수적이다. 먼저, 다양한 웨이블릿 필터를 이용하여 홀로그램 데이터에 대한 주파수 특성 분석을 진행하여 필터 종류에 따른 에너지 집중도를 분석한다. 두 번째로 에너지 집중도를 이용한 부대역 선택 알고리즘에 대해 소개한다. 마지막으로 JPEG2000의 웨이블릿 필터인 Daubechies 9/7을 이용한 JPEG2000, SPIHT, H.264 결과와 제안하는 방법을 이용하여 압축 및 복원하고 압축률 대비 정량적 화질평가를 통해 그 효율을 분석한다.

Keywords

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