Color Domain 및 Gamma Correction 적용에 따른 Retinex 기반 영상개선 알고리즘의 효과 분석
Performance Analysis of Retinex-based Image Enhancement According to Color Domain and Gamma Correction Adaptation
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Retinex-based image enhancement is a technique that utilizes the property that the human visual characteristics are sensitive to the difference from the surrounding pixel value rather than the pixel value itself. These Retinex-based algorithms show different characteristics of the improved image depending on the applied color space or gamma correction. In this paper, we set eight different experimental conditions according to the application of color space and gamma correction, and analyze the objective and subjective performance of each Retinex based image enhancement algorithm and apply it to the implementation of Retinex based algorithm. In the case of gamma correction, quantitative low entropy images and low contrast images are obtained. The application of Retinex technique in HSI color space rather than RGB color space is found to be high in overall subjective image quality as well as maintaining color.
Abstract
Retinex-based image enhancement is a technique that utilizes the property that the human visual characteristics are sensitive to the difference from the surrounding pixel value rather than the pixel value itself. These Retinex-based algorithms show different characteristics of the improved image depending on the applied color space or gamma correction. In this paper, we set eight different experimental conditions according to the application of color space and gamma correction, and analyze the objective and subjective performance of each Retinex based image enhancement algorithm and apply it to the implementation of Retinex based algorithm. In the case of gamma correction, quantitative low entropy images and low contrast images are obtained. The application of Retinex technique in HSI color space rather than RGB color space is found to be high in overall subjective image quality as well as maintaining color.
참고문헌 (11)
- E. Land, "Lightness and retinex theory", Journal of the Optical Society of America, 61(1), pp.1~11 (1971)
- D. Marini, "Computational approach to color adaptation effects", Image and Vision Computing, 18(13), pp.1005~1014 (2000)
- E. Provenzi, "Random spray retinex: A new retinex implementation to investigate the local properties of the model", IEEE Transactions on Image Processing, 16(1), pp.162~171 (2007)
- D.J. Jobson, "Properties and performance of a center", surround retinex, 1997, pp.6(3), 451~462
- A. Moore, "A real-time neural system for color constancy", IEEE Transactions on Neural Networks, 2(2), pp.237~247 (1991)
- W. Ma, "An L1-based variational model for retinex theory and its application to medical images", IEEE Conference on Computer Vision and Pattern Recognition, pp.153~160 (2011)
- J.M. Morel, "A PDE formalization of retinex theory", IEEE Transactions on Image Processing, 19(11), pp.2825~2837 (2010)
- W. Tao, "Enhanced image algorithm at night of improved retinex based on HIS space", International Conference on Intelligent Systems and Knowledge Engineering, pp.1~5 (2017)
- H. Tanaka, "Retinex-based signal enhancement for image dark regions", IEEE International Conference on Signal and Image Processing Applications, pp.205~209 (2017)
- S. Park, "Low-light image enhancement using variational optimization-based retinex model", IEEE Transactions on Consumer Electronics, 63(2), pp.178~184 (2017)
- 김동형, "컬러 이미지 화질 개선을 위한 Retinex 기반의 로그변환 기법", 한국산학기술학회논문지, 19(5), pp.9~16 (2018), 한국산학기술학회[DOI]