한국통신학회논문지 (The Journal of Korean Institute of Communications and Information Sciences)

  • 제38A권3호
  • /
  • Pages.240-248
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  • 2013
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  • 1226-4717(pISSN)
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  • 2287-3880(eISSN)
한국통신학회 (The Korean Institute of Commucations and Information Sciences)
권호 표지
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적응적 가중치 보간법과 이산 웨이블릿 변환을 이용한 효율적인 초해상도 기법

Effective Image Super-Resolution Algorithm Using Adaptive Weighted Interpolation and Discrete Wavelet Transform

  • 임종명 (광운대학교 전자공학과 디지털미디어 연구실) ;
  • 유지상 (광운대학교 전자공학과 디지털미디어 연구실)
  • 투고 : 2012.07.09
  • 심사 : 2013.03.08
  • 발행 : 2013.03.29
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초록

본 논문에서는 이산 웨이블릿 변환(Discrete Wavelet Transform: DWT)과 적응적 가중치 보간법을 이용한 효율적인 초해상도 기법을 제안한다. 기존의 단일 영상에 적용되는 초해상도 기법들의 경우, 영상에서의 고주파 대역을 찾기 위하여 확률 기반의 방법들을 많이 사용하였다. 따라서 연산의 복잡도가 증가하고 처리시간 증가라는 문제점을 발생시킨다. 제안된 기법에서는 고주파 대역을 찾기 위한 방법으로 DWT와 적응적 가중치 보간법을 이용한다. 먼저 주어진 영상에 대하여 DWT를 수행하고, 생성된 고주파 부대역(sub-band)들을 적응적 가중치 보간법을 이용하여 입력 받은 영상과 동일한 크기의 고주파 부대역을 생성한다. 이 부대역들과 입력 받은 영상을 조합하여 이산 웨이블릿 역변환(Inverse DWT : IDWT)을 수행함으로써 고해상도의 영상을 획득하게 된다. 실험을 위하여 원본 영상($512{\times}512$)을 다운 샘플링하여 실험 영상($256{\times}256$)을 획득한다. 실험을 통하여 제안된 기법이 기존의 보간법에 비해 향상된 효율을 보이며, 확률 기반의 기법들과 비슷한 성능을 갖지만 처리시간에서 많은 이득을 보이는 것을 확인할 수 있었다.

In this paper, we propose a super-resolution algorithm using an adaptive weighted interpolation(AWI) and discrete wavelet transform(DWT). In general, super-resolution algorithms for single-image, probability based operations have been used for searching high-frequency components. Consequently, the complexity of the algorithm is increased and it causes the increase of processing time. In the proposed algorithm, we first find high-frequency sub-bands by using DWT. Then we apply an AWI to the obtained high-frequency sub-bands to make them have the same size as the input image. Now, the interpolated high-frequency sub-bands and input image are properly combined and perform the inverse DWT. For the experiments, we use the down-sampled version of the original image($512{\times}512$) as a test image($256{\times}256$). Through experiment, we confirm the improved efficiency of the proposed algorithm comparing with interpolation algorithms and also save the processing time comparing with the probability based algorithms even with the similar performance.

키워드

참고문헌

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