Zero-Reference Image Restoration for Under-Display Camera of UAV
Zhuoran Zheng, Xiuyi Jia, Yunliang Zhuang

TL;DR
This paper introduces a real-time, reference-free image enhancement method for UAV cameras with T-OLED overlays, improving image quality affected by environmental degradation without needing reference images.
Contribution
A novel lightweight, reference-free image restoration network that estimates a low-rank affine grid for enhancing degraded UAV images in real time.
Findings
Effective enhancement of images with T-OLED overlay degradation
No reference image needed for restoration
Real-time processing of arbitrary resolution images
Abstract
The exposed cameras of UAV can shake, shift, or even malfunction under the influence of harsh weather, while the add-on devices (Dupont lines) are very vulnerable to damage. We can place a low-cost T-OLED overlay around the camera to protect it, but this would also introduce image degradation issues. In particular, the temperature variations in the atmosphere can create mist that adsorbs to the T-OLED, which can cause secondary disasters (i.e., more severe image degradation) during the UAV's filming process. To solve the image degradation problem caused by overlaying T-OLEDs, in this paper we propose a new method to enhance the visual experience by enhancing the texture and color of images. Specifically, our method trains a lightweight network to estimate a low-rank affine grid on the input image, and then utilizes the grid to enhance the input image at block granularity. The…
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Taxonomy
TopicsAdvanced Image Processing Techniques · Image Enhancement Techniques · Advanced Vision and Imaging
