首页> 外文会议>Pixels, Objects, Intelligence: GEOgraphic Object Based Image Analysis for the 21st Century >A COMPARISON OF THE PERFORMANCE OF PIXEL-BASED AND OBJECT-BASED CLASSIFICATIONS OVER IMAGES WITH VARIOUS SPATIAL RESOLUTIONS
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A COMPARISON OF THE PERFORMANCE OF PIXEL-BASED AND OBJECT-BASED CLASSIFICATIONS OVER IMAGES WITH VARIOUS SPATIAL RESOLUTIONS

机译:基于像素的基于对象的分类对具有各种空间分辨率的图像的性能的比较

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In the last two decades, advances in computer technology, earth observation sensors and GIS science, led to the development of "Object-based Image Analysis (OBIA)" as an alternative to the traditional pixel-based image analysis method. It was recognized that traditional pixel-based image analysis is limited because of the following reasons: image pixels are not true geographical objects and the pixel topology is limited; pixel based image analysis largely neglects the spatial photo-interpretive elements such as texture, context, and shape; the increased variability implicit within high spatial resolution imagery confuses traditional pixel-based classifiers resulting in lower classification accuracies (Hay and Castilla 2006). Different from pixel-based method, OBIA works on (homogeneous) objects produced by image segmentation and more elements can be used in the classification. As an object is a group of pixels, object characteristics such as mean value, standard deviation, ratio, etc can be calculated; besides there are shape and texture features of the objects available which can be used to differentiate land cover classes with similar spectral information. These extra types of information give OBIA the potential to produce land cover thematic maps with higher accuracies than those produced by traditional pixel-based method. In this paper, we look at the performance of OBIA with different spatial resolution satellite images; comparing the classification results with those produced by the pixel-based method, we intend to find out how spatial resolution of satellite images influences the performance of OBIA. Experiment results showed that with the two sets of images of four different spatial resolutions, object based image analysis obtained higher accuracies than those of the pixel based one; with the increasing of the spatial resolution, the difference in accuracy values between object based and pixel based is decreasing. This paper showed that the object-based image analysis has advantage over the pixel-based one, and in accuracy rating, the advantage was better represented by higher spatial resolution satellite images.
机译:在过去二十年中,计算机技术,地球观测传感器和GIS科学的进步导致了“基于对象的图像分析(OBIA)”的发展,作为传统的基于像素的图像分析方法的替代品。据认识到,传统的基于像素的图像分析受到限制,因为以下原因:图像像素不是真正的地理对象,像素拓扑是有限的;基于像素的图像分析在很大程度上忽略了诸如纹理,上下文和形状的空间照片解释元素;在高空间分辨率图像中隐含的增加的可变性使传统的基于像素的分类器混淆,导致较低的分类精度(Hay和Castilla 2006)。与基于像素的方法不同,OBIA工作由图像分割产生的(均匀)对象,并且可以在分类中使用更多元素。作为对象是一组像素,可以计算诸如平均值,标准偏差,比等的对象特征;此外,可以使用的物体的形状和纹理特征来区分具有相似光谱信息的地覆盖类。这些额外的信息提供了OBIA,可以产生具有更高精度的土地覆盖专题地图,其基于传统像素的方法产生的更高的准确性。在本文中,我们看看OBIA与不同的空间分辨率卫星图像的表现;将分类结果与基于像素的方法产生的分类进行比较,我们打算了解卫星图像的空间分辨率如何影响OBIA的性能。实验结果表明,对于四个不同空间分辨率的两组图像,基于对象的图像分析比基于像素的目标更高的准确性;随着空间分辨率的增加,基于物体和基于像素的基于像素之间的精度值的差异降低。本文认为,基于对象的图像分析具有优于基于像素的一个,并且在精度等级中,优点是由较高的空间分辨率卫星图像表示的优点。

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