Abstract
For producing a single high dynamic range image (HDRI), multiple low dynamic range images (LDRIs) are captured with different exposures and combined. In high dynamic range (HDR) imaging, local motion of objects and noise in a set of LDRIs can influence a final HDRI: local motion of objects causes the ghost artifact and LDRIs, especially captured with under-exposure, make the final HDRI noisy. In this paper, we propose a ghost and noise removal method for HDRI using exposure fusion with subband architecture, in which Haar wavelet filter is used. The proposed method blends weight map of exposure fusion in the subband pyramid, where the weight map is produced for ghost artifact removal as well as exposure fusion. Then, the noise is removed using multi-resolution bilateral filtering. After removing the ghost artifact and noise in subband images, details of the images are enhanced using a gain control map. Experimental results with various sets of LDRIs show that the proposed method effectively removes the ghost artifact and noise, enhancing the contrast in a final HDRI.
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