# Recent Developments from Attribute Profiles for Remote Sensing Image Classification

Source: [Recent Developments from Attribute Profiles for Remote Sensing Image Classification](<https://www.sota2.com/research/paper/68fa642e1e209131cea0340f>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T05:54:50.233Z

Authors: Minh-Tan Pham, S\\'ebastien Lef\\\`evre, Erchan Aptoula, Lorenzo Bruzzone

Published: 2018-03-27T12:22:49.000Z

## Abstract

Morphological attribute profiles (APs) are among the most effective methods to model the spatial and contextual information for the analysis of remote sensing images, especially for classification task. Since their first introduction to this field in early 2010's, many research studies have been contributed not only to exploit and adapt their use to different applications, but also to extend and improve their performance for better dealing with more complex data. In this paper, we revisit and discuss different developments and extensions from APs which have drawn significant attention from researchers in the past few years. These studies are analyzed and gathered based on the concept of multi-stage AP construction. In our experiments, a comparative study on classification results of two remote sensing data is provided in order to show their significant improvements compared to the originally proposed APs.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1803.10036>)

[PDF](<https://arxiv.org/pdf/1803.10036.pdf>)