Hybrid Saturation Restoration for LDR Images of HDR Scenes

• URL: http://arxiv.org/abs/2111.06038v2
• Date: Sun, 14 Nov 2021 08:23:56 GMT
• Title: Hybrid Saturation Restoration for LDR Images of HDR Scenes
• Authors: Chaobing Zheng, Zhengguo Li, and Shiqian Wu
• Abstract summary: In this paper, the saturated regions of the LDR image are restored by fusing model-based and data-driven approaches. 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.
• Score: 18.61019008000831
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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