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Analysis of Color Error and Distortion Pattern in Underwater images

수중 영상의 색상 오차 및 왜곡 패턴 분석

  • Jeong Yeop Kim
  • 김정엽 (영산대학교 성심교양대학)
  • Received : 2024.04.03
  • Accepted : 2024.05.23
  • Published : 2024.06.30
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Abstract

Videos shot underwater are known to have significant color distortion. Typical causes are backscattering by floating objects and attenuation of red colors in proportion to the depth of the water. In this paper, we aim to analyze color correction performance and color distortion patterns for images taken underwater. Backscattering and attenuation caused by suspended matter will be discussed in the next study. In this study, based on the DeepSeeColor model proposed by Jamieson et al., we verify color correction performance and analyze the pattern of color distortion according to changes in water depth. The input images were taken in the US Virgin Islands by Jamieson et al., and out of 1,190 images, 330 images including color charts were used. Color correction performance was expressed as angular error using the input image and the correction image using the DeepSeeColor model. Jamieson et al. calculated the angular error using only black and white patches among the color charts, so they were unable to provide an accurate analysis of overall color distortion. In this paper, the color correction error was calculated targeting the entire color chart patch, so an appropriate degree of color distortion can be suggested. Since the input image of the DeepSeeColor model has a depth of 1 to 8, color distortion patterns according to depth changes can be analyzed. In general, the deeper the depth, the greater the attenuation of red colors. Color distortion due to depth changes was modeled in the form of scale and offset movement to predict distortion due to depth changes. As the depth increases, the scale for color correction increases and the offset decreases. The color correction performance using the proposed method was improved by 41.5% compared to the conventional method.

수중에서 촬영된 영상은 상당한 색상의 왜곡을 수반하는 것으로 알려져 있다. 대표적인 원인은 부유물에 의한 후방 산란(backscattering)과 물의 깊이에 비례하는 적색 계열 색상의 감쇄(attenuation)이다. 본 논문에서는 수중에서 촬영한 영상에 대하여 색상의 보정 성능 및 색상 왜곡의 패턴을 분석하고자 한다. 부유물에 의한 후방 산란과 감쇄 현상에 대해서는 다음 연구에서 다룰 예정이다. 본 연구에서는 Jamieson 등이 제안한 DeepSeeColor 모델을 기반으로 하여, 색상 보정 성능의 검증, 물의 깊이 변화에 따른 색상 왜곡의 패턴을 분석한다. 입력 영상은 Jamieson 등의 미국령 버진 군도(US Virgin Islands)에서 촬영한 것을 이용하였고, 1190여 장 중에서 칼라 차트를 포함하는 330장을 대상으로 한다. 입력 영상과 DeepSeeColor 모델에 의한 보정 영상을 이용하여 색상 보정 성능을 각도 오차(Angular Error)로 표현하였다. Jamieson 등은 칼라 차트 중에서 흑백 패치만을 이용하여 각도 오차를 계산하였기 때문에 전반적인 색상 왜곡에 대한 정확한 분석을 제시하지 못하였다. 본 논문에서는 전체 칼라 차트 패치를 대상으로 하여 색상 보정 오차를 계산하였으므로 적절한 색상 왜곡 정도를 제시할 수 있다. DeepSeeColor 모델의 입력 영상은 1~8까지의 깊이를 가지므로, 깊이 변화에 따른 색상 왜곡 패턴을 분석할 수 있다. 일반적으로는 깊이가 깊어질수록 적색 계열의 색상 감쇄가 크다. 깊이 변화에 따른 색상 왜곡 현상은 스케일과 오프셋 이동의 형태로 모델링 하여 깊이 변화에 따른 왜곡을 예측할 수 있도록 하였다. 깊이가 깊어질수록 색상 보정을 위한 스케일은 증가하였고, 오프셋은 감소하였다. 제안한 방법을 통한 색상 보정의 성능은 기존 방법 대비 41.5% 개선되었다.

Keywords

Acknowledgement

This work was supported by Youngsan University Research Fund of 2024.

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