Title :
A statistical approach for simultaneous segmentation and classification
Author :
Zanotta, Daniel C. ; Ferreira, Matheus P. ; Zorte, Maciel ; Shimabukuro, Yosio
Author_Institution :
Nat. Inst. for Space Res., São José dos Campos, Brazil
Abstract :
This paper presents an alternative object based classification for multispectral remote sensing images. Instead of classifying the images after the segmentation process, it is suggested to involve some steps of objects recognition during the segmentation process in order to improve the final classification results. The methodology is based on the statistical distribution of object classes. Experiments were performed with a TM-Landsat image and the results were compared with a reference data. The results indicate the soundness of the proposed methodology.
Keywords :
geophysical image processing; hyperspectral imaging; image classification; image segmentation; remote sensing; statistical distributions; TM Landsat image; multispectral remote sensing images; object based classification; object class statistical distribution; simultaneous image segmentation-classification; statistical approach; Abstracts; Accuracy; Image resolution; Image segmentation; Merging; Remote sensing; TV; object based classification; pattern recognition; statistical distribution;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6947593