Towards Practical and Efficient High-Resolution HDR Deghosting with CNN

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12366)


Generating High Dynamic Range (HDR) image in the presence of camera and object motion is a tedious task. If uncorrected, these motions will manifest as ghosting artifacts in the fused HDR image. On one end of the spectrum, there exist methods that generate high-quality results that are computationally demanding and too slow. On the other end, there are few faster methods that produce unsatisfactory results. With ever increasing sensor/display resolution, currently we are very much in need of faster methods that produce high-quality images. In this paper, we present a deep neural network based approach to generate high-quality ghost-free HDR for high-resolution images. Our proposed method is fast and fuses a sequence of three high-resolution images (16-megapixel resolution) in about 10 s. Through experiments and ablations, on different publicly available datasets, we show that the proposed method achieves state-of-the-art performance in terms of accuracy and speed.



This work was supported by a project grant from MeitY (No.4(16)/2019-ITEA), Govt. of India and WIRIN.

Supplementary material

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Supplementary material 1 (pdf 40342 KB)


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Authors and Affiliations

  1. 1.Video Analytics LabIndian Institute of ScienceBangaloreIndia

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