Name
Title | ||
|---|---|---|
Modified local variance based method for selecting the optimal spatial resolution of remote sensing image |
Abstract | ||
|---|---|---|
Facing with the prevalence of multi-spatial resolution satellite data sets, selecting data with appropriate resolution has become a new problem. This paper analyses the significance of scale selection of remote sensing images and discusses geostatistics based method of quantitively selecting the optimal spatial resolution of remote sensing image. Breaking through the limitation of traditional average local variance, this paper proposes the modified average local variance method based on variable window size and variable resolution to quantitatively select the optimal spatial resolution of remote sensing image. In order to verify the validity of this method, this paper gives further image classification experiments at different spatial resolution. The experimental results show that the trend of classification accuracy along with spatial resolution is consistent with that of modified average local variance, which means that the image classification accuracy of the optimal resolution image is basically higher than those of other's. Consequently, modified average local variance based method of quantitively selecting the optimal spatial resolution of remote sensing image has theoretical and instructive meaning to a certain extent. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/GEOINFORMATICS.2010.5567566 | Geoinformatics |
Keywords | Field | DocType |
geophysical techniques,remote sensing,variable window size,optimal spatial resolution,scale,variable resolution,remote sensing image,image classification accuracy,spatial resolution,geostatistics,image classification experiments,modified local variance,multispatial resolution satellite data sets,image classification,geophysical image processing,photogrammetry,remote sensing images,modified average local variance method,pixel,accuracy | Iterative reconstruction,Photogrammetry,Pattern recognition,Computer science,Remote sensing,Local variance,Artificial intelligence,Pixel,Contextual image classification,Image resolution,Geostatistics,Variable resolution | Conference |
ISBN | Citations | PageRank |
978-1-4244-7301-4 | 1 | 0.54 |
References | Authors | |
2 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dong-Ping Ming | 1 | 89 | 10.68 |
| Jian-Cheng Luo | 2 | 99 | 20.75 |
| Longxiang Li | 3 | 23 | 2.51 |
| Zhuoqin Song | 4 | 7 | 1.25 |