Journal of KIISE (정보과학회 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Structural Similarity Index for Image Assessment Using Pixel Difference and Saturation Awareness

이미지 평가를 위한 픽셀 변화량과 포화 인지의 구조적 유사도 기법

  • 정지수 (아주대학교 전자공학과) ;
  • 김영진 (아주대학교 전자공학과)
  • Received : 2014.05.19
  • Accepted : 2014.08.14
  • Published : 2014.10.15
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Abstract

Until now, a lot of image quality assessment techniques or tools for optimal human visual system(HVS)-awareness have been researched and SSIM(Structural SIMilarity) and its improved techniques are representative examples. However, they often cannot cope with various images and different distortion types robustly, and thus this can cause a large gap between their index values and HVS-awareness. In this paper, we conduct image quality assessment on SSIM and its variants intensively and analyze the causes of each component function's observed anomalies. Then, we propose a novel image quality assessment technique to compensate and improve such anomalies. Additionally, through extensive image assessment simulations, we show that the proposed technique can indicate HVS-awareness more robustly and consistently than SSIM and its variants for various images and different distortion types.

지금까지 최적의 인간 시각 만족을 위한 이미지 평가 기법 또는 도구 연구가 많이 이루어져 오고 있는데 SSIM(Structural SIMilarity) 및 이의 개선 기법들이 그 대표적인 예이다. 하지만 이들 기법은 여전히 다양한 이미지 종류 및 이미지 왜곡 종류에 대해 견실하게 대응하지 못하는 한계를 보이며 인간 시각 만족과의 괴리가 크게 존재하고 있다. 이 논문에서는 SSIM 및 개선된 SSIM 기법을 대상으로 집중적인 이미지 평가를 수행하였으며 각각의 함수에서의 관측된 이상 동작 내용에 대해서 원인을 분석하고 이를 보완 및 개선하는 새로운 이미지 평가 기법을 제시한다. 또, 기법에 대한 다양한 이미지 평가 실험을 통해서 제안 기법이 SSIM과 이의 기존 개선 기법보다 여러 이미지 종류와 왜곡 종류에 대해서 인간 시각 만족을 견실하고 일관성 있게 효과적으로 표현하고 있음을 보인다.

Keywords

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