Rate-Distortion Optimized Illumination Estimation for Wavelet-Based Video Coding

We propose a rate-distortion optimized framework for estimating illumination changes (lighting variations, fade in/out effects) in a highly scalable coding system. Illumination variations are realized using multiplicative factors in the image domain and are estimated considering the coding cost of t...

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Vydané v:2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) s. 1213 - 1217
Hlavní autori: Haghighat, Maryam, Mathew, Reji, Naman, Aous, Young, Sean, Taubman, David
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.04.2018
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ISSN:2379-190X
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Abstract We propose a rate-distortion optimized framework for estimating illumination changes (lighting variations, fade in/out effects) in a highly scalable coding system. Illumination variations are realized using multiplicative factors in the image domain and are estimated considering the coding cost of the illumination field and input frames which are first subject to a temporal Lifting-based Illumination Adaptive Transform (LIAT). The coding cost is modelled by an ℓ 1 -norm optimization problem which is derived to approximate a quadratic-log function which emerges from rate-distortion considerations. The optimization problem is solved using ADMM. The proposed solution works the same or better than a mesh-based approach proposed in prior work, where sparsity was controlled by explicitly choosing mesh parameters. In the compression-inspired formulation presented here, sparsity is discovered automatically through the solution of a convex program that depends only on a target rate-distortion operating point.
AbstractList We propose a rate-distortion optimized framework for estimating illumination changes (lighting variations, fade in/out effects) in a highly scalable coding system. Illumination variations are realized using multiplicative factors in the image domain and are estimated considering the coding cost of the illumination field and input frames which are first subject to a temporal Lifting-based Illumination Adaptive Transform (LIAT). The coding cost is modelled by an ℓ 1 -norm optimization problem which is derived to approximate a quadratic-log function which emerges from rate-distortion considerations. The optimization problem is solved using ADMM. The proposed solution works the same or better than a mesh-based approach proposed in prior work, where sparsity was controlled by explicitly choosing mesh parameters. In the compression-inspired formulation presented here, sparsity is discovered automatically through the solution of a convex program that depends only on a target rate-distortion operating point.
Author Young, Sean
Haghighat, Maryam
Naman, Aous
Mathew, Reji
Taubman, David
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  fullname: Mathew, Reji
  organization: School of Electrical Engineering and Telecommunications, The University of New South Wales, Australia
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  surname: Young
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  organization: School of Electrical Engineering and Telecommunications, The University of New South Wales, Australia
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  givenname: David
  surname: Taubman
  fullname: Taubman, David
  organization: School of Electrical Engineering and Telecommunications, The University of New South Wales, Australia
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Snippet We propose a rate-distortion optimized framework for estimating illumination changes (lighting variations, fade in/out effects) in a highly scalable coding...
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StartPage 1213
SubjectTerms Distortion
Encoding
Illumination estimation
Lighting
Optimization
R-D optimization
Rate-distortion
Scalable video coding
Wavelet transforms
Wavelet-based coding
Title Rate-Distortion Optimized Illumination Estimation for Wavelet-Based Video Coding
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