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저상관도 측정치와 DCT를 이용한 압축센싱 기반 영상 획득 알고리듬

A Compressive Sensing Based Imaging Algorithm Using Incoherent Measurements and DCT

  • Kim, Seehyun (Department of Information and Communications Engineering, The University of Suwon)
  • 투고 : 2016.09.01
  • 심사 : 2016.09.08
  • 발행 : 2016.10.31

초록

최근 활발히 연구되고 있는 압축센싱 (compressive sensing) 이론에 따르면 나이퀴스트 주파수보다 적은 샘플율으로도 원 신호를 충실히 복원할 수 있음이 알려져 있다. 압축, 전송, 저장 등의 여러 분야에서 압축센싱 방법을 적용하려는 시도가 꾸준히 이어지고 있다. 특히 4K, 8K 등으로 요구되는 화소수가 제곱의 형태로 증가되는 영상처리 분야에서는 압축센싱에 기대하는 바가 크다. 본 논문에서는 압축센싱 기법을 적용한 영상의 획득 알고리듬을 제안한다. 영상의 일반적인 특성을 활용하여 높은 에너지 압축 성능을 가지는 DCT와 저상관도의 특성을 갖는 Noiselet 변환을 결합하여 영상 획득 과정을 구성한다. 원 영상은 2차 콘 프로그램 (SOCP)을 풀어 복원할 수 있다. 여러 영상에 대해 획득 및 복원 성능을 측정 및 비교하였으며 제안된 알고리듬이 우수한 복원 성능을 보임을 알 수 있다.

Compressive sensing has proved that a signal can be restored from less samples than the Nyquist rate. Reducing the required data rate is essential for a variety of fields including compression, transmission, and storage. It has been made lots of attempt to apply the compressive sensing theory into data intensive fields, such as image processing which needs to cover 4K and 8K pictures. In this paper, an image acquisition algorithm based on compressive sensing is proposed. It combines DCT, which can compact the energy of a image into a few coefficients, and the Noiselet transform, which is incoherent with DCT. The DCT coefficients represent the coarse structure of the images while the Noiselet information holds the fine details. Performance experiments with several images show that the proposed image acquisition algorithm not only outperforms the previous results, but also improves the reconstruction quality faster as the number of measurements increases.

키워드

참고문헌

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피인용 문헌

  1. 비지역적 유사성 및 3차원 필터링 기반 영상 잡음제거 vol.21, pp.10, 2016, https://doi.org/10.6109/jkiice.2017.21.10.1886