1st International ICST Workshop on Knowledge Discovery and Data Mining

Research Article

A Remote Sensing Image Fusion Algorithm Based on Ordinal Fast Independent Component Analysis

  • @INPROCEEDINGS{10.4108/wkdd.2008.2690,
        author={Zhongni Wang and Xianchuan Yu and Libao Zhang},
        title={A Remote Sensing Image Fusion Algorithm Based on Ordinal Fast Independent Component Analysis},
        proceedings={1st International ICST Workshop on Knowledge Discovery and Data Mining},
        publisher={ACM},
        proceedings_a={WKDD},
        year={2010},
        month={5},
        keywords={},
        doi={10.4108/wkdd.2008.2690}
    }
    
  • Zhongni Wang
    Xianchuan Yu
    Libao Zhang
    Year: 2010
    A Remote Sensing Image Fusion Algorithm Based on Ordinal Fast Independent Component Analysis
    WKDD
    ACM
    DOI: 10.4108/wkdd.2008.2690
Zhongni Wang1,*, Xianchuan Yu1,*, Libao Zhang1
  • 1: College of Information Science and Technology, Beijing Normal University, Beijing, 100875, China.
*Contact email: bameinini@163.com, Chuan.yu@ieee.org

Abstract

Data fusion on remote sensing is hot in current image processing. The key of a successful image fusion is to find an effective and practical image fusion algorithm. A new approach , that is the ordinal fast independent component analysis for remote image fusion between Landsat ETM+ panchromatic and CBERS multi-spectral images, is proposed to eliminate high-order image data redundancy for two different Remote sensing images. The independent components are done factor analysis, and then the fused image is obtained by applying image fusion rule. Visual and statistical analysis proves that the concept of fusion based on the ordinal fast independent component analysis is promising, and it significantly increases the signal-to-noise ratio and improves the fusion quality.