Combined Convolutional Neural Network for Highly Compressed Images Denoising

Binying Liu, Sei Ichiro Kamata

研究成果: Conference contribution

抄録

Many methods for denoising additive white Gaussian images have been developed, such as the use of non-local mean filters (NLF) and deep convolutional neural networks (CNN). However, these denoising methods still have many limitations on compressed images such as JPEG2000 compression. Based on quantization of noisy wavelet coefficients, JPEG2000 may lead to very specific visual artifacts. This compressed image's noise distribution model is highly spatially correlated and very different from the noise distribution model in additive Gaussian white noise images. In this paper, we propose a convolutional neural network structure combined with nonlocal filter. At first a convolutional neural network have been trained by using highly compressed noisy images to obtain a specific noise model estimation and this noise model estimation is used for the residual neural network. Secondly, it based on non-proximity average filtering, where a similar block selection method is modified to find block artifacts in the compressed image and then do denoising. Finally, combining these two methods can get a clear image output. The evaluation results of this method on the grayscale image dataset are better than the latest technology. Contribution- We produced a noise distribution CNN model that can predict the noise of highly compressed images with complex noise distribution, and combine CNN and Nonlocal mean filters to obtain good denoising results.

本文言語English
ホスト出版物のタイトル2020 Joint 9th International Conference on Informatics, Electronics and Vision and 2020 4th International Conference on Imaging, Vision and Pattern Recognition, ICIEV and icIVPR 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728193311
DOI
出版ステータスPublished - 2020 8 26
イベントJoint 9th International Conference on Informatics, Electronics and Vision and 4th International Conference on Imaging, Vision and Pattern Recognition, ICIEV and icIVPR 2020 - Kitakyushu, Japan
継続期間: 2020 8 262020 8 29

出版物シリーズ

名前2020 Joint 9th International Conference on Informatics, Electronics and Vision and 2020 4th International Conference on Imaging, Vision and Pattern Recognition, ICIEV and icIVPR 2020

Conference

ConferenceJoint 9th International Conference on Informatics, Electronics and Vision and 4th International Conference on Imaging, Vision and Pattern Recognition, ICIEV and icIVPR 2020
国/地域Japan
CityKitakyushu
Period20/8/2620/8/29

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ビジョンおよびパターン認識
  • 情報システム
  • 電子工学および電気工学
  • 器械工学

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