Deep Image Compression using BINet Andr Nortje 18247717@sun.ac.za - - PowerPoint PPT Presentation

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Deep Image Compression using BINet Andr Nortje 18247717@sun.ac.za - - PowerPoint PPT Presentation

Jan 23, 2024 481 likes •608 views

Deep Image Compression using BINet Andr Nortje 18247717@sun.ac.za Prof. Herman Engelbrecht hebrecht@sun.ac.za Dr Herman Kamper kamperh@sun.ac.za 1 The Standard Approach Image Compression JPEG : DCT -> Quantisation Tables ->

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SLIDE 1

Deep Image Compression using BINet

André Nortje 18247717@sun.ac.za

  • Prof. Herman Engelbrecht

hebrecht@sun.ac.za Dr Herman Kamper kamperh@sun.ac.za

1

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SLIDE 2

The Standard Approach

  • Image Compression
  • JPEG : DCT -> Quantisation Tables -> Entropy Coding [3].
  • WebP: like JPEG but with Linear in-painting [1].
  • Problem
  • Standard codecs suffer from arduous hand-tuning of quantisation

parameters and lack of end-to-end system optimisation.

  • Solution
  • Deep Learning ;)
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SLIDE 3

Deep Image Compression

Encoder Decoder B i n

Basic Architecture

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SLIDE 4

Why Patch Based Schemes are Avoided

Block Artefacts

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SLIDE 5

BINet : BINary INpainting Network

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SLIDE 6

Masked BINet: Is inpainting from binary codes possible?

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Inpainting Complexity

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SLIDE 8

Does the ability to inpaint aid compression?

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SLIDE 9

PSNR Compression Curve

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SLIDE 10

Current and Future Work

  • We’ve created a Proof Of Concept … now:
  • Separate inpainting and patch decoder seems to lead to

greater gains.

  • Training the Google Recurrent Model [7] to become a

BINet, attempt beating current S.O.T.A

  • Application of BINet to Error Correction/ Detection

systems.

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SLIDE 11

References

  • 1. WebP : A new Image Format for the Web (2016) [Website]. Available at https://developers.google.com/speed/webp/docs/compression (Accessed:

2018-07-30)

  • 2. Cisco (2015), Cisco Visual Networking Index: Forecast and Methodology, 2016-2021 [Journal Article]. Available at https://www.cisco.com/c/en/us/

solutions/collateral/service-provider/visual-networking-index-vni/complete-white-paper-c11-481360.html#_Toc484813971 (Accessed: 2018-08-23)

  • 3. G. Wallace (1991), The JPEG Compression Standard, Communications of the ACM, Available at http://www.ijg.org/files/Wallace.JPEG.pdf

(Accessed: 2018-07-31)

  • 4. Iain E. Richardson, The H.264 Standard Video Compression Standard 2nd Edition, Vcodex Limited Uk, Available at https://files.cnblogs.com/files/

irish/The_H.264_advanced_video_compression_standard.pdf (Accessed: 2018-07-31)

  • 5. T. Raiko, M. Berglund, G. Alain et al. (2014), Techniques for Learning Binary Stochastic Feedforward Neural Networks, Available at https://arxiv.org/

pdf/1406.2989.pdf (Accessed: 2018-07-31)

  • 6. G. Toderici, S. O’Malley, S. Hwang et al. (2015), Variable Rate Image Compression with Recurrent Neural Networks, Available at http://arxiv.org/abs/

1511.06085 (Accessed: 2018-07-31)

  • 7. G. Toderici, D. Vincent, N. Johnston (2016), Full Resolution Image Compression with Recurrent Neural Networks, Available at https://arxiv.org/abs/

1608.05148 (Accessed: 2018-01-25)