In this paper an evaluation of the influence of luminance L* at the L*a*b* color space during color segmentation is presented. A comparative study is made between the behavior of segmentation in color images using onl...In this paper an evaluation of the influence of luminance L* at the L*a*b* color space during color segmentation is presented. A comparative study is made between the behavior of segmentation in color images using only the Euclidean metric of a* and b* and an adaptive color similarity function defined as a product of Gaussian functions in a modified HSI color space. For the evaluation synthetic images were particularly designed to accurately assess the performance of the color segmentation. The testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. From the results is obtained that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume.展开更多
Visible and infrared image fusion(VIF)aims to combine information from visible and infrared images into a single fused image.Previous VIF methods usually employ a color space transformation to keep the hue and saturat...Visible and infrared image fusion(VIF)aims to combine information from visible and infrared images into a single fused image.Previous VIF methods usually employ a color space transformation to keep the hue and saturation from the original visible image.However,for fast VIF methods,this operation accounts for the majority of the calculation and is the bottleneck preventing faster processing.In this paper,we propose a fast fusion method,FCDFusion,with little color deviation.It preserves color information without color space transformations,by directly operating in RGB color space.It incorporates gamma correction at little extra cost,allowing color and contrast to be rapidly improved.We regard the fusion process as a scaling operation on 3D color vectors,greatly simplifying the calculations.A theoretical analysis and experiments show that our method can achieve satisfactory results in only 7 FLOPs per pixel.Compared to state-of-theart fast,color-preserving methods using HSV color space,our method provides higher contrast at only half of the computational cost.We further propose a new metric,color deviation,to measure the ability of a VIF method to preserve color.It is specifically designed for VIF tasks with color visible-light images,and overcomes deficiencies of existing VIF metrics used for this purpose.Our code is available at https://github.com/HeasonLee/FCDFusion.展开更多
文摘In this paper an evaluation of the influence of luminance L* at the L*a*b* color space during color segmentation is presented. A comparative study is made between the behavior of segmentation in color images using only the Euclidean metric of a* and b* and an adaptive color similarity function defined as a product of Gaussian functions in a modified HSI color space. For the evaluation synthetic images were particularly designed to accurately assess the performance of the color segmentation. The testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. From the results is obtained that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume.
基金supported by the National Natural Science Foundation of China under Grant Nos.62171038,61827901,and 62088101.
文摘Visible and infrared image fusion(VIF)aims to combine information from visible and infrared images into a single fused image.Previous VIF methods usually employ a color space transformation to keep the hue and saturation from the original visible image.However,for fast VIF methods,this operation accounts for the majority of the calculation and is the bottleneck preventing faster processing.In this paper,we propose a fast fusion method,FCDFusion,with little color deviation.It preserves color information without color space transformations,by directly operating in RGB color space.It incorporates gamma correction at little extra cost,allowing color and contrast to be rapidly improved.We regard the fusion process as a scaling operation on 3D color vectors,greatly simplifying the calculations.A theoretical analysis and experiments show that our method can achieve satisfactory results in only 7 FLOPs per pixel.Compared to state-of-theart fast,color-preserving methods using HSV color space,our method provides higher contrast at only half of the computational cost.We further propose a new metric,color deviation,to measure the ability of a VIF method to preserve color.It is specifically designed for VIF tasks with color visible-light images,and overcomes deficiencies of existing VIF metrics used for this purpose.Our code is available at https://github.com/HeasonLee/FCDFusion.
