Deep Atrous Guided Filter for Image Restoration in Under Display Cameras

• URL: http://arxiv.org/abs/2008.06229v2
• Date: Tue, 1 Sep 2020 06:15:45 GMT
• Title: Deep Atrous Guided Filter for Image Restoration in Under Display Cameras
• Authors: Varun Sundar, Sumanth Hegde, Divya Kothandaraman and Kaushik Mitra
• Abstract summary: Under Display Cameras present a promising opportunity for phone manufacturers to achieve bezel-free displays by positioning the camera behind semi-transparent OLED screens. Such imaging systems suffer from severe image degradation due to light attenuation and diffraction effects. We present Deep Atrous Guided Filter (DAGF), a two-stage, end-to-end approach for image restoration in UDC systems.
• Score: 18.6418313982586
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Under Display Cameras present a promising opportunity for phone manufacturers to achieve bezel-free displays by positioning the camera behind semi-transparent OLED screens. Unfortunately, such imaging systems suffer from severe image degradation due to light attenuation and diffraction effects. In this work, we present Deep Atrous Guided Filter (DAGF), a two-stage, end-to-end approach for image restoration in UDC systems. A Low-Resolution Network first restores image quality at low-resolution, which is subsequently used by the Guided Filter Network as a filtering input to produce a high-resolution output. Besides the initial downsampling, our low-resolution network uses multiple, parallel atrous convolutions to preserve spatial resolution and emulates multi-scale processing. Our approach's ability to directly train on megapixel images results in significant performance improvement. We additionally propose a simple simulation scheme to pre-train our model and boost performance. Our overall framework ranks 2nd and 5th in the RLQ-TOD'20 UDC Challenge for POLED and TOLED displays, respectively.

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