Dual-Camera Joint Deblurring-Denoising
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Abstract (arXiv)
Recent image enhancement methods have shown the advantages of using a pair of long and short-exposure images for low-light photography. These image modalities offer complementary strengths and weaknesses. The former yields an image that is clean but blurry due to camera or object motion, whereas the latter is sharp but noisy due to low photon count. Motivated by the fact that modern smartphones come equipped with multiple rear-facing camera sensors, we propose a novel dual-camera method for obtaining a high-quality image. Our method uses a synchronized burst of short exposure images captured by one camera and a long exposure image simultaneously captured by another. Having a synchronized short exposure burst alongside the long exposure image enables us to (i) obtain better denoising by using a burst instead of a single image, (ii) recover motion from the burst and use it for motion-aware deblurring of the long exposure image, and (iii) fuse the two results to further enhance quality. Our method is able to achieve state-of-the-art results on synthetic dual-camera images from the GoPro dataset with five times fewer training parameters compared to the next best method. We also show that our method qualitatively outperforms competing approaches on real synchronized dual-camera captures.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 35 of its 80 references that are in the map. First posted on arXiv 16 Sep 2023.
Builds on
35 of 80 references.
References · 35
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
- 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 5,045
- 2017Deformable Convolutional Networkscited by 1,488
- 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,358
- 2017PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volumecited by 968
- 2016Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurringcited by 727
- 2017FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoisingcited by 510
- 2019DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Bettercited by 362
- 2018Toward Convolutional Blind Denoising of Real Photographscited by 274
- 2018Unprocessing Images for Learned Raw Denoisingcited by 250
- 2019Deep Stacked Hierarchical Multi-patch Network for Image Deblurringcited by 206
- 2019Real Image Denoising with Feature Attentioncited by 176
23 more
- 2020Human-Aware Motion Deblurringcited by 175
- 2017Burst Denoising with Kernel Prediction Networkscited by 157
- 2015Learning a Convolutional Neural Network for Non-uniform Motion Blur Removalcited by 149
- 2020Defocus Deblurring Using Dual-Pixel Datacited by 139
- 2020A Physics-based Noise Formation Model for Extreme Low-light Raw Denoisingcited by 138
- 2019FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimationcited by 128
- 2021Deep Burst Super-Resolutioncited by 83
- 2016From Motion Blur to Motion Flow: a Deep Learning Solution for Removing Heterogeneous Motion Blurcited by 81
- 2020Learning Event-Based Motion Deblurringcited by 81
- 2018Deep Semantic Face Deblurringcited by 80
- 2017Deep Burst Denoisingcited by 49
- 2022Dancing under the stars: video denoising in starlightcited by 47
- 2019Basis Prediction Networks for Effective Burst Denoising with Large Kernelscited by 46
- 2021Deep Reparametrization of Multi-Frame Super-Resolution and Denoisingcited by 39
- 2022BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignmentcited by 32
- 2020Exposure Trajectory Recovery from Motion Blurcited by 31
- 2021Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Burstscited by 21
- 2020Low-light Image Restoration with Short- and Long-exposure Raw Pairscited by 18
- 2022Face Deblurring using Dual Camera Fusion on Mobile Phonescited by 18
- 2017Motion Deblurring in the Wildcited by 17
- 2022Self-Supervised Image Restoration with Blurry and Noisy Pairscited by 17
- 2022D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restorationcited by 14
- 2018Iterative Residual CNNs for Burst Photography Applicationscited by 9
Built on by
Citing papers per year: 2024: 1; 2025: 2; 2026: 3.
6 papers.
- 2024CRNet: A Detail-Preserving Network for Unified Image Restoration and Enhancement Taskcited by 6
- 2025Grounding Degradations in Natural Language for All-In-One Video Restorationcited by 3
- 2025R3: Reconstruction, Raw, and Rain: Deraining Directly in the Bayer Domaincited by 0
- 2026Dynamic Exposure Burst Image Restorationcited by 0
- 2026Dual-Exposure Imaging with Eventscited by 0
- 2026A Benchmark for Heterogeneous Stereo Deblurring with Physically- and Epipolar-constrained Cross Attentioncited by 0
- 2026A Benchmark for Heterogeneous Stereo Deblurring with Physically- and Epipolar-constrained Cross Attention24 Jun 2026
- 2026Dual-Exposure Imaging with Events11 Apr 2026
- 2026Dynamic Exposure Burst Image Restoration23 Mar 2026
- 2025R3: Reconstruction, Raw, and Rain: Deraining Directly in the Bayer Domain28 Sep 2025
- 2025Grounding Degradations in Natural Language for All-In-One Video Restoration20 Jul 2025
- 2024CRNet: A Detail-Preserving Network for Unified Image Restoration and Enhancement Task22 Apr 2024