Local Inverse Tone Mapping for Scalable High Dynamic Range Image Coding

Page view(s)
32
Checked on Jan 14, 2025
Local Inverse Tone Mapping for Scalable High Dynamic Range Image Coding
Title:
Local Inverse Tone Mapping for Scalable High Dynamic Range Image Coding
Journal Title:
IEEE Transactions on Circuits and Systems for Video Technology
Keywords:
Publication Date:
07 May 2021
Citation:
Z. Wei; C. Wen; Z. Li, "Local Inverse Tone Mapping for Scalable High Dynamic Range Image Coding," in IEEE Transactions on Circuits and Systems for Video Technology , vol.PP, no.99, pp.1-1 doi: 10.1109/TCSVT.2016.2611944
Abstract:
Tone mapping operators (TMOs) and inverse tone mapping operators (iTMOs) are important for scalable coding of high dynamic range (HDR) images. Because of the highly nonlinearity of local TMOs, it is very difficult to estimate the iTMO accurately for a local TMO. In this paper, we present a twolayer local iTMO estimation algorithm using an edge-preserving decomposition technique. The low dynamic range (LDR) image is first linearized and then decomposed into a base layer and a detail layer via a fast edge-preserving decomposition method. The base layer of the HDR image is generated by subtracting the LDR detail layer from the HDR image. An iTMO function is finally estimated by solving a novel quadratic optimization problem formulated on the pair of base layers rather than the pair of HDR and LDR images as in existing methods. Experimental results show that the proposed two-layer iTMO can recover the HDR accurately so that it is possible to use these local TMOs in scalable HDR image coding schemes.
License type:
PublisherCopyrights
Funding Info:
Description:
(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISSN:
1051-8215
1558-2205
Files uploaded: