首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >A REVIEW ON SPATIAL QUALITY ASSESSMENT METHODS FOR EVALUATION OF PAN-SHARPENED SATELLITE IMAGERY
【24h】

A REVIEW ON SPATIAL QUALITY ASSESSMENT METHODS FOR EVALUATION OF PAN-SHARPENED SATELLITE IMAGERY

机译:泛尖锐卫星图像评估空间质量评估方法综述

获取原文
       

摘要

Nowadays, high-resolution fused satellite imagery is widely used in multiple remote sensing applications. Although the spectral quality of pan-sharpened images plays an important role in many applications, spatial quality becomes more important in numerous cases. The high spatial quality of the fused image is essential for extraction, identification and reconstruction of significant image objects, and will result in producing high-quality large scale maps especially in the urban areas. This paper introduces the most sensitive and effective methods in detecting the spatial distortion of fused images by implementing a number of spatial quality assessment indices that are utilized in the field of remote sensing and image processing. In this regard, in order to recognize the ability of quality assessment indices for detecting the spatial distortion quantity of fused images, input images of the fusion process are affected by some intentional spatial distortions based on non-registration error. The capabilities of the investigated metrics are evaluated on four different fused images derived from Ikonos and WorldView-2 initial images. Achieved results obviously explicate that two methods namely Edge Variance Distortion and the spatial component of QNR metric called Ds are more sensitive and responsive to the imported errors.
机译:如今,高分辨率融合卫星图像广泛用于多个遥感应用。虽然PAN尖锐的图像的光谱质量在许多应用中起着重要作用,但空间质量在许多情况下变得更加重要。融合图像的高空间质量对于提取,识别和重建显着的图像对象是必不可少的,并且将导致在城市地区产生高质量的大规模地图。本文介绍了通过实现在遥感和图像处理领域中使用的许多空间质量评估指标来检测融合图像的空间失真的最敏感和有效的方法。在这方面,为了识别用于检测融合图像的空间失真量的质量评估指标的能力,融合过程的输入图像受到基于非登记误差的一些有意的空间扭曲的影响。调查指标的能力在来自IKONOS和WorldView-2初始图像的四个不同融合图像上进行评估。实现结果明显阐述了两种方法,即边缘方差失真和名为DS的QNR度量的空间分量更敏感并响应导入错误。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号