针对高动态范围(HDR)图像显示于普通显示设备的问题,提出一种新的基于多尺度分解的色调映射(TM)算法。首先利用局部边缘保留(LEP)滤波器对HDR图像进行多尺度分解,有效平滑了图像的细节同时保留了突出的边缘;根据分解后各层的特点和压缩...针对高动态范围(HDR)图像显示于普通显示设备的问题,提出一种新的基于多尺度分解的色调映射(TM)算法。首先利用局部边缘保留(LEP)滤波器对HDR图像进行多尺度分解,有效平滑了图像的细节同时保留了突出的边缘;根据分解后各层的特点和压缩的要求,提出一个带参数的动态范围压缩函数,通过变化参数以便压缩图像的粗尺度层并增强细尺度层,从而压缩图像的动态范围并增强细节;最后重组各层并恢复颜色,所得到的映射后图像具有良好的视觉效果。实验结果证明,该方法在自然度、结构保真度和整体的质量评价上都要优于Gu等(GU B,LI W J,ZHU M Y,et al.Local edge-preserving multiscale decomposition for high dynamic range image tone mapping[J].IEEE Transactions on Image Processing,2013,22(1):70-79)和Yeganeh等(YEGANEH H,WANG Z.Objective quality assessment of tone-mapped images[J].IEEE Transactions on Image Processing,2013,22(2):657-667)提出的方法,同时也避免了局部色调映射算法所普遍存在的光晕效应。该算法可以用于HDR图像的色调映射。展开更多
We present a method of generating high dynamic range(HDR)radiance maps from a single low dynamic range(LDR)image and its camera response function(CRF).The method first models and estimates the inverse CRF and then mul...We present a method of generating high dynamic range(HDR)radiance maps from a single low dynamic range(LDR)image and its camera response function(CRF).The method first models and estimates the inverse CRF and then multiplies the inverse CRF by a weighting function to make it smooth near the maximum and minimum pixel values,and finally conducts the smooth inverse CRF on the input LDR image to generate HDR image.In the method,the inverse CRF is estimated using one single LDR image and an empirical model of CRF,based on measured RGB distributions at color edges.Unlike most existing methods,the proposed method expands image from both high and low luminance regions.Thus,the algorithm can avoid the artifacts and detail loss in dark area which results from extending image only from bright region.Extensive experimental results show that the approach induces less contrast distortion and produces high visual quality HDR image.展开更多
文摘针对高动态范围(HDR)图像显示于普通显示设备的问题,提出一种新的基于多尺度分解的色调映射(TM)算法。首先利用局部边缘保留(LEP)滤波器对HDR图像进行多尺度分解,有效平滑了图像的细节同时保留了突出的边缘;根据分解后各层的特点和压缩的要求,提出一个带参数的动态范围压缩函数,通过变化参数以便压缩图像的粗尺度层并增强细尺度层,从而压缩图像的动态范围并增强细节;最后重组各层并恢复颜色,所得到的映射后图像具有良好的视觉效果。实验结果证明,该方法在自然度、结构保真度和整体的质量评价上都要优于Gu等(GU B,LI W J,ZHU M Y,et al.Local edge-preserving multiscale decomposition for high dynamic range image tone mapping[J].IEEE Transactions on Image Processing,2013,22(1):70-79)和Yeganeh等(YEGANEH H,WANG Z.Objective quality assessment of tone-mapped images[J].IEEE Transactions on Image Processing,2013,22(2):657-667)提出的方法,同时也避免了局部色调映射算法所普遍存在的光晕效应。该算法可以用于HDR图像的色调映射。
基金supported by the National Natural Science Foundation of China (61401072)
文摘We present a method of generating high dynamic range(HDR)radiance maps from a single low dynamic range(LDR)image and its camera response function(CRF).The method first models and estimates the inverse CRF and then multiplies the inverse CRF by a weighting function to make it smooth near the maximum and minimum pixel values,and finally conducts the smooth inverse CRF on the input LDR image to generate HDR image.In the method,the inverse CRF is estimated using one single LDR image and an empirical model of CRF,based on measured RGB distributions at color edges.Unlike most existing methods,the proposed method expands image from both high and low luminance regions.Thus,the algorithm can avoid the artifacts and detail loss in dark area which results from extending image only from bright region.Extensive experimental results show that the approach induces less contrast distortion and produces high visual quality HDR image.
