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Hybrid Saturation Restoration for LDR Images of HDR Scenes

Authors :
Zheng, Chaobing
Li, Zhengguo
Wu, Shiqian
Publication Year :
2021

Abstract

There are shadow and highlight regions in a low dynamic range (LDR) image which is captured from a high dynamic range (HDR) scene. It is an ill-posed problem to restore the saturated regions of the LDR image. In this paper, the saturated regions of the LDR image are restored by fusing model-based and data-driven approaches. With such a neural augmentation, two synthetic LDR images are first generated from the underlying LDR image via the model-based approach. One is brighter than the input image to restore the shadow regions and the other is darker than the input image to restore the high-light regions. Both synthetic images are then refined via a novel exposedness aware saturation restoration network (EASRN). Finally, the two synthetic images and the input image are combined together via an HDR synthesis algorithm or a multi-scale exposure fusion algorithm. The proposed algorithm can be embedded in any smart phones or digital cameras to produce an information-enriched LDR image.<br />Comment: arXiv admin note: text overlap with arXiv:2007.02042

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2111.06038
Document Type :
Working Paper