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AWNet: Attentive Wavelet Network for Image ISP

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Computer Vision – ECCV 2020 Workshops (ECCV 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12537))

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Abstract

As the revolutionary improvement being made on the performance of smartphones over the last decade, mobile photography becomes one of the most common practices among the majority of smartphone users. However, due to the limited size of camera sensors on phone, the photographed image is still visually distinct to the one taken by the digital single-lens reflex (DSLR) camera. To narrow this performance gap, one is to redesign the camera image signal processor (ISP) to improve the image quality. Owing to the rapid rise of deep learning, recent works resort to the deep convolutional neural network (CNN) to develop a sophisticated data-driven ISP that directly maps the phone-captured image to the DSLR-captured one. In this paper, we introduce a novel network that utilizes the attention mechanism and wavelet transform, dubbed AWNet, to tackle this learnable image ISP problem. By adding the wavelet transform, our proposed method enables us to restore favorable image details from RAW information and achieve a larger receptive field while remaining high efficiency in terms of computational cost. The global context block is adopted in our method to learn the non-local color mapping for the generation of appealing RGB images. More importantly, this block alleviates the influence of image misalignment occurred on the provided dataset. Experimental results indicate the advances of our design in both qualitative and quantitative measurements. The source code is available at https://github.com/Charlie0215/AWNet-Attentive-Wavelet-Network-for-Image-ISP.

L. Dai and X. Liu—Contributed equally.

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Author information

Authors and Affiliations

  1. McMaster University, Hamilton, ON, Canada

    Linhui Dai, Xiaohong Liu, Chengqi Li & Jun Chen

Authors
  1. Linhui Dai
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  2. Xiaohong Liu
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  3. Chengqi Li
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  4. Jun Chen
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Corresponding author

Correspondence to Linhui Dai .

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Editors and Affiliations

  1. University of Clermont Auvergne, Clermont Ferrand, France

    Adrien Bartoli

  2. Università degli Studi di Udine, Udine, Italy

    Andrea Fusiello

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Dai, L., Liu, X., Li, C., Chen, J. (2020). AWNet: Attentive Wavelet Network for Image ISP. In: Bartoli, A., Fusiello, A. (eds) Computer Vision – ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science(), vol 12537. Springer, Cham. https://doi.org/10.1007/978-3-030-67070-2_11

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  • DOI: https://doi.org/10.1007/978-3-030-67070-2_11

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  • Online ISBN: 978-3-030-67070-2

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