Classification in High Resolution Images with Multiple Classifiers

A. Monadjemi, B.T. Thomas, and M. Mirmehdi (UK)


Image Classification, High Resolution images, High Frequency Analysis, Multiple classifiers.


We examine the use of high frequency features in high resolution images and demonstrate how they can increase texture classification accuracy when used in combination with lower frequency features. We used eight features, four low frequency and four high frequency, derived from patches of 4032 2688images. Furthermore, we experiment with both single and multiple classifiers to illustrate the effectiveness of such a combination. Outcomes of classification tests on outdoor scene patches are presented and discussed.

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