Journal Article

GSDerainNet: A Deep Network Architecture Based on a Gaussian Shannon Filter for Single Image Deraining

Yao, Yanji, Shi, Zhimin, Li, Jing, Wang, Guocheng, Hu, Huiwen, Liu, Lintao

2023

Overview

With the continuous advancement of target detection technology in remote sensing, target detection technology in images captured by drones has performed well. However, object detection in drone imagery is still a challenge under rainy conditions. Rain is a common severe weather condition, and rain streaks often degrade the image quality of sensors. The main issue of rain streaks removal from a single image is to prevent over smoothing (or underclearing) phenomena. Aiming at the above problems, this paper proposes a deep learning (DL)-based rain streaks removal framework called GSDerainNet, which properly formulates the single image rain streaks removal problem; rain streaks removal is aptly described as a Gaussian Shannon (GS) filter-based image decomposition problem. The GS filter is a novel filter proposed by us, which consists of a parameterized Gaussian function and a scaled Shannon function. Two-dimensional GS filters exhibit high stability and effectiveness in dividing an image into low- and high-frequency parts. In our framework, an input image is first decomposed into a low-frequency part and a high-frequency part by using the GS filter. Rain streaks are located in the high-frequency part. We extract and separate the rain features of the high-frequency part through a deep convolutional neural network (CNN). The experimental results obtained on synthetic data and real data show that the proposed method can better suppress the morphological artifacts caused by filtering. Compared with state-of-the-art single image rain streaks removal methods, the proposed method retains finer image object structures while removing rain streaks.

• Publisher: MDPI AG
• Subject: Artificial intelligence / Artificial neural networks / Comparative analysis / Computer architecture / convolutional neural network (CNN) / Datasets / Decomposition / Deep learning / deep learning (DL) / Dictionaries / Filters (Mathematics) / Gaussian Shannon (GS) filter / Identification and classification / Image degradation / Image filters / Image processing / Image quality / image rain removal / Machine learning / Methods / Morphology / Neural networks / normal distribution / Object recognition / Rain / Rain and rainfall / Remote sensing / Severe weather / Synthetic data / Target detection / Technology application / Weather