The Journal of the Korea Contents Association (한국콘텐츠학회논문지)

The Korea Contents Association (한국콘텐츠학회)
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Moving Picture Compression using Frame Classification by Luminance Characteristics

명암특성에 따른 프레임 분류를 이용한 동영상 압축기법

  • 김상현 (경북대학교 산업전자전기공학부)
  • Received : 2010.11.11
  • Accepted : 2011.04.12
  • Published : 2011.04.28
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Abstract

This paper proposes an efficient moving picture compression for video sequences with luminance variations. In the proposed algorithm, the luminance variation parameters are estimated and local motions are compensated. To detect the frame required luminance compensation, we employ the frame classification based on the cross entropy between histograms of two successive frames, which can reduce the computational redundancy. Simulation results show that the proposed method yields a higher peak signal to noise ratio (PSNR) than that of the conventional methods, with a low computational load, when the video scene contains large luminance variations.

본 논문은 명암 변화가 심한 비디오 시퀀스에 대해 효율적인 동영상 압축기법을 제안한다. 제안한 알고리즘에서는 화면간의 명암 변화 변수들을 추정하고 지역적인 움직임 보상을 수행한다. 밝기 보상이 필요한 화면을 검출하기 위하여 연속되는 두 프레임간의 히스토그램의 크로스 엔트로피를 계산하여 프레임 분류를 하고 명암 변화가 심한 화면에 대해서만 밝기 보상을 수행하여 명암 변화가 심하지 않은 경우에 발생할 수 있는 불필요한 계산량을 줄였다. 명암 변화가 심한 비디오 시퀀스에 대한 실험결과 제안한 알고리즘은 기존의 알고리즘에 비해 적은 계산량으로 높은 PSNR (peak signal to noise ratio) 성능을 나타내었다.

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References

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