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Research on Image Denoising Adaptive Algorithm for UAV Based on Visual Landing Cover

Research on Image Denoising Adaptive Algorithm for UAV Based on Visual Landing

By: Pengrui Qiu,  Xiping Yuan,  Shu Gan and  Yu Lin  
Open Access
|Apr 2018

Abstract

UAV autonomous landing refers to the UAV lands on only depending on airborne navigation equipment and flight control system, and ultimately achieves a safe landing. To achieve self-landing, UAV must have the ability to self-navigation and positioning, so that the high-precision visual navigation positioning technology is the key to achieve UAV self-landing technology.This paper concentrating on the noise effects on the pictures obtained during visual landing process of UAV, it has introduced the gravity of classical physics to image pixel, come up with a mathematical expression for the strength of gravity between pixels, then conformed the adaptive window by the gravity between pixels and performed corresponding filtering processing. It is shown by the experimental results that this algorithm has a great improvement on image denoising and detail preserving when compared with the traditional median filtering and switching median filtering algorithms.

Language: English
Page range: 114 - 117
Published on: Apr 24, 2018
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2018 Pengrui Qiu, Xiping Yuan, Shu Gan, Yu Lin, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution 4.0 License.