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End-to-end optimization of nonlinear transform codes for perceptual quality
Open accessAbstract
We introduce a general framework for end-to-end optimization of the rate-distortion performance of nonlinear transform codes assuming scalar quantization. The framework can be used to optimize any differentiable pair of analysis and synthesis transforms in combination with any differentiable perceptual metric. As an example, we consider a code built from a linear transform followed by a form of multi-dimensional local gain control. Distortion is measured with a state-of-the-art perceptual metric. When optimized over a large database of images, this representation offers substantial improvements in bitrate and perceptual appearance over fixed (DCT) codes, and over linear transform codes optimized for mean squared error.
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Cited by
Conditional Probability Models for Deep Image Compression
Mentzer, F., Agustsson, E., Tschannen, M., Timofte, R., & Gool, L. V. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00462 · Cited by 490
Image and Video Compression With Neural Networks: A Review
Ma, S., Zhang, X., Jia, C., Zhao, Z., Wang, S., & Wang, S. (2020) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2910119 · Cited by 459
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations
Agustsson, E., Mentzer, F., Tschannen, M., Cavigelli, L., Timofte, R., Benini, L., & Van Gool, L. (2017) · arXiv · doi:10.48550/arxiv.1704.00648 · Cited by 403
Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics
Duan, L., Liu, J., Yang, W., Huang, T., & Gao, W. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3016485 · Cited by 260
Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff
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Metadata
- Authors
- Ballé, J., Laparra, V., & Simoncelli, E. P.
- Venue
- 2016 Picture Coding Symposium (PCS)
- Publisher
- IEEE
- Published
- 2016
- Pages
- 1-5
- OpenAlex
- W2490784316
- Cited by
- 261
- References
- 6
- FWCI
- 5.05
- Type
- conference paper
- Language
- en
- Open access
- green
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