The application and implementation of the plane subdivision
model in remote sensing image mosaic
ABSTRACT
With the rapid development and widespread application of remote sensing
technology, the amount of remote sensing image data has shown an explosive growth
trend. As an important part of the remote sensing data processing workflow, remote
sensing image mosaicking aims to spatially register and color balance multiple remote
sensing images with overlapping areas, thereby generating a large-scale seamless
mosaic of remote sensing images.However, traditional remote sensing image
mosaicking methods often face challenges such as large computational volume and low
processing efficiency when dealing with large-scale and high-resolution remote sensing
data.Therefore, researching and developing efficient and fast remote sensing image
mosaicking methods have important theoretical and practical significance.
The planar partition model, as an efficient spatial data partitioning method, has
been widely applied in fields such as geographic information systems and computer
graphics in recent years. This model significantly improves the efficiency and
performance of data processing by recursively dividing spatial data into multiple sub-
regions and processing each sub-region independently. In remote sensing image
mosaicking, introducing the planar partition model is expected to divide large-scale
remote sensing images into multiple small, easily processed blocks, thereby achieving
efficient and fast mosaicking processing.
This paper aims to delve into the application and implementation of the planar
partition model in remote sensing image mosaicking. Firstly, the paper will introduce
the background, significance, and research and technical route design. Secondly, it will
elaborate on the basic principles of the planar partition model and its applicability in
remote sensing image processing. Finally,it will detail the specific application method
of the planar partition model in remote sensing image mosaicking. Through
experimental verification, the paper will demonstrate the significant advantages of the
planar partition model in improving the efficiency and quality of remote sensing image
mosaicking, and provide prospects for future research directions.
