Modified hierarchical k-nearest neighbor method with application to land-cover classification

Tatsuya Hayashi; Hakaru Tamukoh; Ryosuke Kubota

doi:10.1117/12.2521356

22 March 2019 Modified hierarchical k-nearest neighbor method with application to land-cover classification

Tatsuya Hayashi, Hakaru Tamukoh, Ryosuke Kubota

Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 110493R (2019) https://doi.org/10.1117/12.2521356
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

Abstract

In this paper, we propose a land-cover classification method based on a modified hierarchical k-nearest neighbor (MHkNN) algorithm to achieve a high classification accuracy. The proposed method introduces a reliability measure for each training sample, which is defined as confidence in the sample belonging to each of the considered classes. The method performs the majority voting considering not only the number of the training samples, but also their reliabilities. The classification performance of the proposed method is compared to that of the conventional land-cover classification methods. The effectiveness of the proposed method is verified by applying it to real remote sensing images.

Citation Download Citation

Tatsuya Hayashi, Hakaru Tamukoh, and Ryosuke Kubota "Modified hierarchical k-nearest neighbor method with application to land-cover classification", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110493R (22 March 2019); https://doi.org/10.1117/12.2521356

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