Rough Clustering Based Unsupervised Image Change Detection

📝 Original Info

• Title: Rough Clustering Based Unsupervised Image Change Detection
• ArXiv ID: 1404.6071
• Date: 2014-04-25
• Authors: Researchers from original ArXiv paper

📝 Abstract

This paper introduces an unsupervised technique to detect the changed region of multitemporal images on a same reference plane with the help of rough clustering. The proposed technique is a soft-computing approach, based on the concept of rough set with rough clustering and Pawlak's accuracy. It is less noisy and avoids pre-deterministic knowledge about the distribution of the changed and unchanged regions. To show the effectiveness, the proposed technique is compared with some other approaches.

💡 Deep Analysis

Deep Dive into Rough Clustering Based Unsupervised Image Change Detection.

This paper introduces an unsupervised technique to detect the changed region of multitemporal images on a same reference plane with the help of rough clustering. The proposed technique is a soft-computing approach, based on the concept of rough set with rough clustering and Pawlak’s accuracy. It is less noisy and avoids pre-deterministic knowledge about the distribution of the changed and unchanged regions. To show the effectiveness, the proposed technique is compared with some other approaches.

📄 Full Content

Reference