Quality evaluation for dual-band color fusion images based on scene understanding

Gao Shaoshu; Jin Weiqi; Wang Lingxue; Luo Yuan; Li Jiakun

Volume 43 Issue 1

Jan. 2014

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Article Navigation > Infrared and Laser Engineering > 2014 > 43(1): 300-305

Gao Shaoshu, Jin Weiqi, Wang Lingxue, Luo Yuan, Li Jiakun. Quality evaluation for dual-band color fusion images based on scene understanding[J]. Infrared and Laser Engineering, 2014, 43(1): 300-305.

Citation:

Gao Shaoshu, Jin Weiqi, Wang Lingxue, Luo Yuan, Li Jiakun. Quality evaluation for dual-band color fusion images based on scene understanding[J]. Infrared and Laser Engineering, 2014, 43(1): 300-305.

Quality evaluation for dual-band color fusion images based on scene understanding

1.
MoE Key Laboratory of Photoelectronic Imaging Technology and System,School of Optoelectronics,Beijing Institute of Technology,Beijing 100081,China;
2.
College of Computer and Communication Engineering,China University of Petroleum,Qingdao 266580,China

Received Date: 2013-05-11
Rev Recd Date: 2013-06-12
Publish Date: 2014-01-25

Abstract

Image quality assessments are the basis for evaluations of dual-band color fusion algorithms and systems. A method of quality evaluation for visible and infrared color fusion images was explored. A comprehensive evaluation metric, image perceptual quality based on scene understanding (PQSU) was proposed, and color fusion images of three typical scenes were selected to perform a psychophysical experiment. The prediction model of PQSU was derived by multiple linear regression analysis of the experimental data for conventional image quality metrics and the proposed evaluation metric. The results show that the positive correlation between color harmony and color naturalness is very high. The variation of PQSU can be predicted effectively by color harmony and sharpness. In the three image categories, the proportional coefficients in prediction models for PQSU are different; whereas, the basic forms of Image quality assessments are the basis for evaluations of dual-band color fusion algorithms and systems. A method of quality evaluation for visible and infrared color fusion images was explored. A comprehensive evaluation metric, image perceptual quality based on scene understanding (PQSU) was proposed, and color fusion images of three typical scenes were selected to perform a psychophysical experiment. The prediction model of PQSU was derived by multiple linear regression analysis of the experimental data for conventional image quality metrics and the proposed evaluation metric. The results show that the positive correlation between color harmony and color naturalness is very high. The variation of PQSU can be predicted effectively by color harmony and sharpness. In the three image categories, the proportional coefficients in prediction models for PQSU are different; whereas, the basic forms of prediction models are unchanged. The proposed comprehensive evaluation metric and its prediction model provide a foundation for further developing objective quality evaluation of color fusion images.
- quality evaluation,
- color fusion,
- psychophysical experiment,
- evaluation metric

References

[1]	Choi S Y, Luo M R, Pointer M R, et al. Investigation of large display color image appearance I: important factors affecting perceived quality [J]. Journal of Imaging Science and Technology, 2008, 25(4): 040904.
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[3]	Pedersen M, Bonnier N, Hardeberg J Y, et al. Attributes of image quality for color prints [J]. Journal of Electronic Imaging, 2010, 19(1): 011016.
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[7]	Toet A, Schoumans N, Ijspeert J K. Perceptual evaluation of different nighttime imaging modalities [C]//Proc of Information Fusion, 2000, 1: TUD3- 17-TUD3-23.
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[12]	Shi Junsheng, Jin Weiqi, Wang Lingxue. Study on perceptual evaluation of fusion image quality for color night vision[J]. Journal Infrared Millimeter and Waves, 2005, 24(3): 236-240. (in Chinese) 石俊生, 金伟其, 王岭雪. 视觉评价夜视彩色融合图像质量的实验研究[J]. 红外与毫米波学报, 2005, 24(3): 236-240.
[13]
[14]	Krebs W K, Sinai M J. Psychophysical assessments of image-sensor fused imagery [J]. Human Factors, 2002, 44: 257-271.
[15]	Xu Guili, Liu Xiaoxia, Tian Yupeng, et al. Image clarity- evaluation-function method[J]. Infrared and Laser Engineering, 2009, 38(1): 180-184. (in Chinese) 徐贵力, 刘小霞, 田裕鹏, 等. 一种图像清晰度评价方法[J]. 红外与激光工程, 2009, 38(1): 180-184.
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[18]	Caviedes J, Oberti F. A new sharpness metric based on local kurtosis, edge and energy information[J]. Signal Processing: Image Communication, 2004, 19: 147-161.
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[20]	Guan Shingsheng, Hung Posung. Influences of psychological factors on image color preferences evaluation [J]. Color Research and Application, 2010, 35(3): 213-232.
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[22]	Burchett K E. Color harmony [J]. Color Research and Application, 2002, 27(1): 28-31.
[23]	Yendrikhovskij S N, Blommaert F J J, Ridder H. Color reproduction and the naturalness constraint[J]. Color Research and Application, 1999, 24(1): 52-67.
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[25]	Toet A, Walraven J. New false color mapping for image fusion[J]. Optical Engineering, 1996, 35(3): 650-658.
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[29]	Wang Lingxue, Shi Shiming, Jin Weiqi, et al. Hot targets enhancement for color fusion of visible and infrared image[J]. Transactions of Beijing Institute of Technology, 2008, 28(1): 1-4. (in Chinese) 王岭雪, 史世明, 金伟其, 等. 可见光与红外图像彩色融合中的热目标增强方法[J]. 北京理工大学学报, 2008, 28(1):1-4.
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[32]	Shi Shiming, Wang Lingxue, Jin Weiqi, et al. A dual-band color imaging system for visible and thermal IR images based on color transfer in YUV color space [J]. Acta Armamentarii, 2009, 30(1): 30-35. (in Chinese) 史世明, 王岭雪, 金伟其, 等. 基于YUV 空间色彩传递的可见光/热成像双通道彩色成像系统[J]. 兵工学报, 2009, 30(1): 30-35.
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[34]	Shi Shiming, Wang Lingxue, Jin Weiqi, et al. Natural-color- appearance steerable pyramid color fusion for visible and IR images [J]. Journal of Optoelectronics Laser, 2009, 20 (11): 1552-1560. (in Chinese) 史世明, 王岭雪, 金伟其, 等. 自然感色彩的可见光/红外控向金字塔融合[J]. 光电子激光, 2009, 20(11): 1552-1560.
[35]	Shi Shiming, Wang Lingxue, Jin Weiqi, et al. Color night vision based on color transfer in YUV color space[C]//SPIE, 2008, 6623: 66230B.
[36]
[37]
[38]	Shi Shiming, Wang Lingxue, Jin Weiqi, et al. Color night vision research based on multi-resolution color transfer [J]. Acta Photonica Sinica, 2010, 39(3): 553-558. (in Chinese) 史世明, 王岭雪, 金伟其, 等. 基于多分辨率色彩传递的彩色夜视方法研究[J]. 光子学报, 2010, 39(3): 553-558.
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[41]	Berns R S. Methods for characterizing CRT displays [J]. Displays, 1996, 16: 173-182.
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[43]	ITU -R Recommendation BT.500 -12. Methodology for the subjective assessment of the quality of the television pictures[S]. 2010.
[44]	Draper N R, Smith H. Applied Regression Analysis [M]. 3d ed. New York: John Wiley Sons, Inc, 1998: 335-345.

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通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

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Quality evaluation for dual-band color fusion images based on scene understanding

1. MoE Key Laboratory of Photoelectronic Imaging Technology and System,School of Optoelectronics,Beijing Institute of Technology,Beijing 100081,China;

2. College of Computer and Communication Engineering,China University of Petroleum,Qingdao 266580,China

Received Date: 2013-05-11

Rev Recd Date: 2013-06-12

Publish Date: 2014-01-25

Key words:

Abstract: Image quality assessments are the basis for evaluations of dual-band color fusion algorithms and systems. A method of quality evaluation for visible and infrared color fusion images was explored. A comprehensive evaluation metric, image perceptual quality based on scene understanding (PQSU) was proposed, and color fusion images of three typical scenes were selected to perform a psychophysical experiment. The prediction model of PQSU was derived by multiple linear regression analysis of the experimental data for conventional image quality metrics and the proposed evaluation metric. The results show that the positive correlation between color harmony and color naturalness is very high. The variation of PQSU can be predicted effectively by color harmony and sharpness. In the three image categories, the proportional coefficients in prediction models for PQSU are different; whereas, the basic forms of Image quality assessments are the basis for evaluations of dual-band color fusion algorithms and systems. A method of quality evaluation for visible and infrared color fusion images was explored. A comprehensive evaluation metric, image perceptual quality based on scene understanding (PQSU) was proposed, and color fusion images of three typical scenes were selected to perform a psychophysical experiment. The prediction model of PQSU was derived by multiple linear regression analysis of the experimental data for conventional image quality metrics and the proposed evaluation metric. The results show that the positive correlation between color harmony and color naturalness is very high. The variation of PQSU can be predicted effectively by color harmony and sharpness. In the three image categories, the proportional coefficients in prediction models for PQSU are different; whereas, the basic forms of prediction models are unchanged. The proposed comprehensive evaluation metric and its prediction model provide a foundation for further developing objective quality evaluation of color fusion images.

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Reference (44)

[1]	Choi S Y, Luo M R, Pointer M R, et al. Investigation of large display color image appearance I: important factors affecting perceived quality [J]. Journal of Imaging Science and Technology, 2008, 25(4): 040904.
[2]
[3]	Pedersen M, Bonnier N, Hardeberg J Y, et al. Attributes of image quality for color prints [J]. Journal of Electronic Imaging, 2010, 19(1): 011016.
[4]
[5]
[6]	Essock E A, Sinai M J, McCarley J S, et al. Perceptual ability with real-world nighttime scenes: image-intensified, infrared and fused-color imagery [J]. Human Factors, 1999, 41: 438.
[7]	Toet A, Schoumans N, Ijspeert J K. Perceptual evaluation of different nighttime imaging modalities [C]//Proc of Information Fusion, 2000, 1: TUD3- 17-TUD3-23.
[8]
[9]
[10]	Toet A, Frankenb E M. Perceptual evaluation of different image fusion schemes [J]. Displays, 2003, 24: 25-37.
[11]
[12]	Shi Junsheng, Jin Weiqi, Wang Lingxue. Study on perceptual evaluation of fusion image quality for color night vision[J]. Journal Infrared Millimeter and Waves, 2005, 24(3): 236-240. (in Chinese) 石俊生, 金伟其, 王岭雪. 视觉评价夜视彩色融合图像质量的实验研究[J]. 红外与毫米波学报, 2005, 24(3): 236-240.
[13]
[14]	Krebs W K, Sinai M J. Psychophysical assessments of image-sensor fused imagery [J]. Human Factors, 2002, 44: 257-271.
[15]	Xu Guili, Liu Xiaoxia, Tian Yupeng, et al. Image clarity- evaluation-function method[J]. Infrared and Laser Engineering, 2009, 38(1): 180-184. (in Chinese) 徐贵力, 刘小霞, 田裕鹏, 等. 一种图像清晰度评价方法[J]. 红外与激光工程, 2009, 38(1): 180-184.
[16]
[17]
[18]	Caviedes J, Oberti F. A new sharpness metric based on local kurtosis, edge and energy information[J]. Signal Processing: Image Communication, 2004, 19: 147-161.
[19]
[20]	Guan Shingsheng, Hung Posung. Influences of psychological factors on image color preferences evaluation [J]. Color Research and Application, 2010, 35(3): 213-232.
[21]
[22]	Burchett K E. Color harmony [J]. Color Research and Application, 2002, 27(1): 28-31.
[23]	Yendrikhovskij S N, Blommaert F J J, Ridder H. Color reproduction and the naturalness constraint[J]. Color Research and Application, 1999, 24(1): 52-67.
[24]
[25]	Toet A, Walraven J. New false color mapping for image fusion[J]. Optical Engineering, 1996, 35(3): 650-658.
[26]
[27]	Waxman A M, Gove A N, Fay D A, et al. Night vision: opponent processing in the fusion of visible and IR imagery[J]. Neural Networks, 1997, 10(1): 1-6.
[28]
[29]	Wang Lingxue, Shi Shiming, Jin Weiqi, et al. Hot targets enhancement for color fusion of visible and infrared image[J]. Transactions of Beijing Institute of Technology, 2008, 28(1): 1-4. (in Chinese) 王岭雪, 史世明, 金伟其, 等. 可见光与红外图像彩色融合中的热目标增强方法[J]. 北京理工大学学报, 2008, 28(1):1-4.
[30]
[31]
[32]	Shi Shiming, Wang Lingxue, Jin Weiqi, et al. A dual-band color imaging system for visible and thermal IR images based on color transfer in YUV color space [J]. Acta Armamentarii, 2009, 30(1): 30-35. (in Chinese) 史世明, 王岭雪, 金伟其, 等. 基于YUV 空间色彩传递的可见光/热成像双通道彩色成像系统[J]. 兵工学报, 2009, 30(1): 30-35.
[33]
[34]	Shi Shiming, Wang Lingxue, Jin Weiqi, et al. Natural-color- appearance steerable pyramid color fusion for visible and IR images [J]. Journal of Optoelectronics Laser, 2009, 20 (11): 1552-1560. (in Chinese) 史世明, 王岭雪, 金伟其, 等. 自然感色彩的可见光/红外控向金字塔融合[J]. 光电子激光, 2009, 20(11): 1552-1560.
[35]	Shi Shiming, Wang Lingxue, Jin Weiqi, et al. Color night vision based on color transfer in YUV color space[C]//SPIE, 2008, 6623: 66230B.
[36]
[37]
[38]	Shi Shiming, Wang Lingxue, Jin Weiqi, et al. Color night vision research based on multi-resolution color transfer [J]. Acta Photonica Sinica, 2010, 39(3): 553-558. (in Chinese) 史世明, 王岭雪, 金伟其, 等. 基于多分辨率色彩传递的彩色夜视方法研究[J]. 光子学报, 2010, 39(3): 553-558.
[39]
[40]
[41]	Berns R S. Methods for characterizing CRT displays [J]. Displays, 1996, 16: 173-182.
[42]
[43]	ITU -R Recommendation BT.500 -12. Methodology for the subjective assessment of the quality of the television pictures[S]. 2010.
[44]	Draper N R, Smith H. Applied Regression Analysis [M]. 3d ed. New York: John Wiley Sons, Inc, 1998: 335-345.

Quality evaluation for dual-band color fusion images based on scene understanding

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