Journal of Broadcast Engineering (방송공학회논문지)

The Korean Institute of Broadcast and Media Engineers (한국방송∙미디어공학회)
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Local Differential Pixel Assessment Method for Image Stitching

영상 스티칭의 지역 차분 픽셀 평가 방법

  • Rhee, Seongbae (Department of Electronic Engineering, KyungHee University) ;
  • Kang, Jeonho (Department of Electronic Engineering, KyungHee University) ;
  • Kim, Kyuheon (Department of Electronic Engineering, KyungHee University)
  • Received : 2019.07.29
  • Accepted : 2019.09.23
  • Published : 2019.09.30
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Abstract

Image stitching is a technique for solving the problem of narrow field of view of a camera by composing multiple images. Recently, as the use of content such as Panorama, Super Resolution, and 360 VR increases, the need for faster and more accurate image stitching technology is increasing. So far, many algorithms have been proposed to satisfy the required performance, but the objective evaluation method for measuring the accuracy has not been standardized. In this paper, we present the problems of PSNR and SSIM(Structural similarity index method) measurement methods and propose a Local Differential Pixel Mean method. The LDPM evaluation method that includes geometric similarity and brightness measurement information is proved through a test, and the advantages of the evaluation method are revealed through comparison with SSIM.

영상 스티칭은 다수의 영상을 합성하여 카메라의 좁은 시야각(Field of View) 문제를 해결하는 기술이다. 최근 동영상 기반 Panorama, Super Resolution, 360 VR(Virtual Reality) 등의 콘텐츠 사용이 증가함에 따라, 보다 빠르고 정확한 영상 스티칭 기술의 필요성이 커지고 있다. 또한, 지금까지 필요 성능을 만족시키기 위해 많은 알고리즘이 제안되고 있지만, 정확성을 측정하는 객관적 평가 방법은 표준화되지 않고 있다. 최근에서야 PSNR(Peak signal-to-noise ratio)과 SSIM(Structural similarity index method) 측정값을 제시하는 방법이 주를 이루고 있지만, 본 논문에서는 PSNR과 SSIM 측정 방식의 문제점을 밝히고, 해당 방법의 한계점을 극복하여 기하적 유사성과 광도 측정 정보를 포괄하는 지역 차분 픽셀 평가(LDPM: Local differential pixel mean)방법을 제안한다. 또한, 본 논문에서 제안하는 LDPM(Local differential pixel mean) 평가 방식을 테스트 영상을 통해 증명하고 SSIM과 비교를 통해 해당 평가 방법의 이점을 밝힌다.

Keywords

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