Interactive Pansharpening and Active Classification in Remote Sensing

Pablo Ruiz*, Javier Mateos, Gustavo Camps-Valls, Rafael Molina, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter presents two multimodal prototypes for remote sensing image classification where user interaction is an important part of the system. The first one applies pansharpening techniques to fuse a panchromatic image and a multispectral image of the same scene to obtain a high resolution (HR) multispectral image. Once the HR image has been classified the user can interact with the system to select a class of interest. The pansharpening parameters are then modified to increase the system accuracy for the selected class without deteriorating the performance of the classifier on the other classes. The second prototype utilizes Bayesian modeling and inference to implement active learning and parameter estimation in a binary kernel-based multispectral classification schemes. In the prototype we developed three different strategies for selecting the more informative pixel to be included in the training set. In the experimental section, the prototypes are described and applied to two real multispectral image classification problems.

Original languageEnglish (US)
Title of host publicationMultimodal Interaction in Image and Video Applications
EditorsAngel Sappa, Jordi Vitria
Pages67-81
Number of pages15
DOIs
StatePublished - Oct 21 2013

Publication series

NameIntelligent Systems Reference Library
Volume48
ISSN (Print)1868-4394
ISSN (Electronic)1868-4408

ASJC Scopus subject areas

  • Computer Science(all)
  • Information Systems and Management
  • Library and Information Sciences

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