Abstract
To investigate the effect of pixel-to-pixel correlation on classification performance for TM data, some experiments were conducted. One result was that the pixel-to-pixel correlation in homogeneous fields of TM data is larger than that of the simultaneously acquired MSS data, a finding that implies it is more important to consider the pixel correlation for TM classification rather than MSS classification.To overcome the effect of the correlation, the following methods were investigated. Based on the autoregressive model, the Gaussian statistical parameters for the correlated image were modified to those for uncorrelated stochastic process. An example using agricultural TM data shows a slight improvement in terms of the weighted mean percentage of correct classification. By investigating the correlation structures, a more realistic model for TM data was realized.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
