Neighborhood Feature Pooling for Remote Sensing Image Classification

• URL: http://arxiv.org/abs/2510.25077v2
• Date: Thu, 30 Oct 2025 01:37:51 GMT
• Title: Neighborhood Feature Pooling for Remote Sensing Image Classification
• Authors: Fahimeh Orvati Nia, Amirmohammad Mohammadi, Salim Al Kharsa, Pragati Naikare, Zigfried Hampel-Arias, Joshua Peeples,
• Abstract summary: Neighborhood feature pooling is a novel texture feature extraction method for remote sensing image classification.<n>The NFP layer captures relationships between neighboring inputs and efficiently aggregates local similarities across feature dimensions.
• Score: 1.6932802756478729
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this work, we propose neighborhood feature pooling (NFP) as a novel texture feature extraction method for remote sensing image classification. The NFP layer captures relationships between neighboring inputs and efficiently aggregates local similarities across feature dimensions. Implemented using convolutional layers, NFP can be seamlessly integrated into any network. Results comparing the baseline models and the NFP method indicate that NFP consistently improves performance across diverse datasets and architectures while maintaining minimal parameter overhead.

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