标题：Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data
作者：Li, Lin; Luo, Heng; Zhu, Haihong
来源出版物：REMOTE SENSING 卷：6 期：5 页：4409-4429 DOI：10.3390/rs6054409 出版年：MAY 2014
摘要：Image quality is important for taking full advantage of satellite data. As a common indicator, the National Imagery Interpretability Scale (NIIRS) is widely used for image quality assessment and provides a comprehensive representation of image quality from the perspective of interpretability. The ZY-3 (Ziyuan-3) satellite is the first civil high resolution mapping satellite in China, which was established in 2012. So far, there has been no reports on adopting NIIRS as the common indicator for the quality assessment of that satellite image data. This lack of a common quality indicator results in a gap between satellite data users around the world and those in China regarding the understanding of the quality and usability of ZY-3 data. To overcome the gap, using the general image-quality equation (GIQE), this study evaluates the ZY-3 sensor-corrected (SC) panchromatic nadir (NAD) data in terms of the NIIRS. In order to solve the uncertainty resulting from the exceeding of the ground sample distance (GSD) of ZY-3 data (2.1 m) in GIQE (less than 2.03 m), eight images are used to establish the relationship between the manually obtained NIIRS and the GIQE predicted NIIRS. An adjusted GIQE is based on the relationship and verified by another five images. Our study demonstrates that the method of using adjusted GIQE for calculating NIIRS can be used for the quality assessment of ZY-3 satellite images and reveals that the NIIRS value of ZY-3 SC NAD data is about 2.79.
入藏号：WOS:000337160700042
文献类型：Article
语种：English
作者关键词：image quality, interpretability, NIIRS, GIQE, linear regression analysis, ZY-3
扩展关键词：SPATIAL-RESOLUTION; QUALITY
通讯作者地址：Luo, Heng;Wuhan Univ, Sch Resource & Environm Sci, Wuhan
430079, Peoples R China.
电子邮件地址：lilin@whu.edu.cn; luoheng@whu.edu.cn; hhzhu@whu.edu.cn
地址：
[Li, Lin; Luo, Heng; Zhu, Haihong] Wuhan Univ, Sch Resource & Environm Sci, Wuhan
430079, Peoples R China.
研究方向：Remote Sensing
ISSN：2072-4292
