2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDSS-IVC-DL.8
Paper Title Sandwiched image compression: Wrapping neural networks around a standard codec
Authors Onur Guleryuz, Phil Chou, Hugues Hoppe, Danhang Tang, Ruofei Du, Philip Davidson, Sean Fanello, Google LLC, United States
SessionSS-IVC-DL: Special Session: Optimized Image and Video Coding Using Deep Learning
LocationArea B
Session Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Poster
Topic Special Sessions: Optimized image and video coding schemes using deep learning
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Abstract We sandwich a standard image codec between two neural networks: a preprocessor that outputs neural codes, and a postprocessor that reconstructs the image. The neural codes are compressed as ordinary images by the standard codec. Using differentiable proxies for both rate and distortion, we develop a rate-distortion optimization framework that trains the networks to generate neural codes that are efficiently compressible as images. This architecture not only improves rate-distortion performance for ordinary RGB images, but also enables efficient compression of alternative image types (such as normal maps of computer graphics) using standard image codecs. Results demonstrate the effectiveness and flexibility of neural processing in mapping a variety of input data modalities to the rigid structure of standard codecs. This versatility is so much so that rate-distortion-optimized neural processing seamlessly learns to transport color images using a single-channel (grayscale) codec.