Work

IBEWMS: Individual Band Spectral Feature Enhancement-Based Waterfront Environment AAV Multispectral Image Stitching

Year: 2024

Type: article

Abstract: As the use of autonomous aerial vehicles (AAVs) for waterfront monitoring increases, combining multiple AAV multispectral (MS) images into a single, seamless panoramic image has become crucial. This process ensures the accuracy and effectiveness of waterfront monitoring. However, the varying reflective properties of different wavelengths bring challenges for existing single-band MS image stitching frameworks, especially in complex waterfront areas. To address this challenge, we developed the individual band enhanced waterfront multispectral stitching (IBEWMS) framework. Central to this framework is the individual band spectral feature enhancement (IBSFE) module, which enhances each spectral band based on varying reflectance of different land covers, yielding clearer and more reliable features. Using IBSFE, we designed a detector-free framework to effectively extract and match feature points in waterfront MS images. In addition, we implemented an image fusion technique to address issues, such as ghosting and global reflectance inconsistency, in panoramic images. To support this work, we provided the Wuhan AAV Waterfront Environment MS Dataset, comprising 12 315 high-resolution 5-band MS images. Experiments show that IBEWMS outperforms both deep learning and traditional stitching frameworks, offering valuable support for downstream applications.

Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

DOI: 10.1109/jstars.2024.3493883

Authors: Zixuan Yang, Fangling Pu, Hongjia Chen, Yangpeng He, Xin Xu

Institution: Wuhan University

Language: English

Topic: Advanced Image Fusion Techniques

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,496

Funder: National Natural Science Foundation of China