红外与激光工程
紅外與激光工程
홍외여격광공정
INFRARED AND LASER ENGINEERING
2014年
1期
300-305
,共6页
高绍姝%金伟其%王岭雪%骆媛%李家琨
高紹姝%金偉其%王嶺雪%駱媛%李傢琨
고소주%금위기%왕령설%락원%리가곤
质量评价%彩色融合%主观评价%评价指标
質量評價%綵色融閤%主觀評價%評價指標
질량평개%채색융합%주관평개%평개지표
quality evaluation%color fusion%psychophysical experiment%evaluation metric
图像质量评价是双波段彩色融合处理算法及系统评价的基础,文中研究了一种可见光与红外彩色融合图像质量评价方法。提出了基于场景理解的图像感知质量PQSU综合评价指标,选择三类典型场景彩色融合图像进行了主观视觉评价实验;通过对已有评价指标与PQSU综合指标的主观评价实验结果进行多元线性回归分析,建立了PQSU的预测模型。结果表明:融合图像的场景颜色协调性与自然感高度相关;利用图像清晰度和颜色协调性可以有效地预测PQSU;针对不同场景类型,已有评价指标在PQSU的预测模型中所占的权重有所不同,但预测模型的基本形式保持不变。文中提出的PQSU及其预测模型为进一步发展融合图像质量客观评价模型奠定了基础。
圖像質量評價是雙波段綵色融閤處理算法及繫統評價的基礎,文中研究瞭一種可見光與紅外綵色融閤圖像質量評價方法。提齣瞭基于場景理解的圖像感知質量PQSU綜閤評價指標,選擇三類典型場景綵色融閤圖像進行瞭主觀視覺評價實驗;通過對已有評價指標與PQSU綜閤指標的主觀評價實驗結果進行多元線性迴歸分析,建立瞭PQSU的預測模型。結果錶明:融閤圖像的場景顏色協調性與自然感高度相關;利用圖像清晰度和顏色協調性可以有效地預測PQSU;針對不同場景類型,已有評價指標在PQSU的預測模型中所佔的權重有所不同,但預測模型的基本形式保持不變。文中提齣的PQSU及其預測模型為進一步髮展融閤圖像質量客觀評價模型奠定瞭基礎。
도상질량평개시쌍파단채색융합처리산법급계통평개적기출,문중연구료일충가견광여홍외채색융합도상질량평개방법。제출료기우장경리해적도상감지질량PQSU종합평개지표,선택삼류전형장경채색융합도상진행료주관시각평개실험;통과대이유평개지표여PQSU종합지표적주관평개실험결과진행다원선성회귀분석,건립료PQSU적예측모형。결과표명:융합도상적장경안색협조성여자연감고도상관;이용도상청석도화안색협조성가이유효지예측PQSU;침대불동장경류형,이유평개지표재PQSU적예측모형중소점적권중유소불동,단예측모형적기본형식보지불변。문중제출적PQSU급기예측모형위진일보발전융합도상질량객관평개모형전정료기출。
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.