Assessment of micro-vibrations effect on the quality of remote sensing satellites images

IF 1.8 Q3 REMOTE SENSING

International Journal of Image and Data Fusion Pub Date : 2023-01-16 DOI:10.1080/19479832.2023.2167874

Mohamed A. Ali, F. Eltohamy, Adel Abd-Elrazek, Mohamed Hanafy

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引用次数: 1

Abstract

ABSTRACT Recently, there is a growing interest in analysing the degrading effect of satellite micro-vibrations due to the rapid growth in satellite technologies and the urgent need to precisely extract a huge amount of information from satellite images. Different kinds of micro-vibration have a notable effect on the quality of satellite images. The main objective of this paper is to demonstrate and analyse the effect of all types of micro-vibration on the quality of images acquired by high-resolution satellites. An algorithm to simulate micro-vibrations is proposed. A very high-resolution satellite image from the Pleiades-neo satellite is selected as an example to be used in addressing the degrading effects of micro-vibrations. In this paper, the modulation transfer function (MTF) is used as a major function to model the degradation that has been conducted. Also, several quality metrics are used to quantitatively assess the degradation. The key result of this paper is the significant effect of micro-vibrations on the quality of remote sensing satellite images which is attributed to the main influential parameters. These parameters like blur diameter, vibration displacement, number of Time Delay and Integration (TDI) stages of the camera, and the ratio of the integration time to the vibration period.

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微振动对遥感卫星图像质量影响的评估

摘要近年来，由于卫星技术的快速发展和从卫星图像中精确提取大量信息的迫切需要，人们对分析卫星微振动的衰减效应越来越感兴趣。不同类型的微振动对卫星图像质量有显著影响。本文的主要目的是证明和分析所有类型的微振动对高分辨率卫星获取的图像质量的影响。提出了一种模拟微振动的算法。选择昂宿星团新卫星的一张非常高分辨率的卫星图像作为例子，用于解决微振动的退化影响。在本文中，调制传递函数（MTF）被用作对已经进行的退化进行建模的主要函数。此外，还使用了几个质量指标来定量评估退化情况。本文的关键结果是微振动对遥感卫星图像质量的显著影响，这归因于主要的影响参数。这些参数如模糊直径、振动位移、相机的时间延迟和积分（TDI）级的数量，以及积分时间与振动周期的比率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Image and Data Fusion REMOTE SENSING-

CiteScore

5.00

自引率

0.00%

发文量

期刊介绍： International Journal of Image and Data Fusion provides a single source of information for all aspects of image and data fusion methodologies, developments, techniques and applications. Image and data fusion techniques are important for combining the many sources of satellite, airborne and ground based imaging systems, and integrating these with other related data sets for enhanced information extraction and decision making. Image and data fusion aims at the integration of multi-sensor, multi-temporal, multi-resolution and multi-platform image data, together with geospatial data, GIS, in-situ, and other statistical data sets for improved information extraction, as well as to increase the reliability of the information. This leads to more accurate information that provides for robust operational performance, i.e. increased confidence, reduced ambiguity and improved classification enabling evidence based management. The journal welcomes original research papers, review papers, shorter letters, technical articles, book reviews and conference reports in all areas of image and data fusion including, but not limited to, the following aspects and topics: • Automatic registration/geometric aspects of fusing images with different spatial, spectral, temporal resolutions; phase information; or acquired in different modes • Pixel, feature and decision level fusion algorithms and methodologies • Data Assimilation: fusing data with models • Multi-source classification and information extraction • Integration of satellite, airborne and terrestrial sensor systems • Fusing temporal data sets for change detection studies (e.g. for Land Cover/Land Use Change studies) • Image and data mining from multi-platform, multi-source, multi-scale, multi-temporal data sets (e.g. geometric information, topological information, statistical information, etc.).