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
基金supported by the National Natural Science Foundation of China(Nos.51875227,51805261,51775267)the Natural Science Foundation of Jiangsu Province(Nos.BK20181286,BK20180430)the Aviation Science Fund(No.20161552014)
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.
