Joint High Dynamic Range Imaging and Color Demosaicing

A non-parametric high dynamic range (HDR) fusion approach is proposed that works on raw images of singlesensor color imaging devices which incorporate the Bayer pattern. Thereby the non-linear opto-electronic conversion function (OECF) is recovered before color demosaicing, so that interpolation artifacts do not affect the photometric calibration. Graph-based segmentation greedily clusters the exposure set into regions of roughly constant radiance in order to regularize the OECF estimation. The segmentation works on Gaussian-blurred sensor images, whereby the artificial gray value edges caused by the Bayer pattern are smoothed away. With the OECF known the 32-bit HDR radiance map is reconstructed by weighted summation from the differently exposed raw sensor images. Because the radiance map contains lower sensor noise than the individual images, it is finally demosaiced by weighted bilinear interpolation which prevents the interpolation across edges. Here, the previous segmentation results from the photometric calibration are utilized. After demosaicing, tone mapping is applied, whereby remaining interpolation artifacts are further damped due to the coarser tonal quantization of the resulting image.