IDA: Improving distribution analysis for reducing data complexity and dimensionality in hyperspectral images

Dalal AL-Alimi, Mohammed Abdulaziz Aide Al-qaness, Zhihua Cai, Eman Ahmed Alawamy

Abstract: Highlights•A noverl feature extraction method to reduce HSI dimensions, called IDA is proposed.•IDA is applied to improve data correlation and distribution and classes variance.•Study the impact of feature extraction and preproccesing on the HSI classification.•Using different datasets with well-known exisiting methods to test the IDA.