Analysis of Four Remote Image Fusion Algorithms for Landsat7 ETM+ PAN and Multi-spectral Imagery

Yuan De Bao,Zha Yanbo,Yu Shiwei,Li Lianjian,Hong Xueqian

doi:10.3991/ijoe.v10i3.3686

Abstract

This study takes the southeastern part of Beijing as an example to compare four remote image fusion algorithms for improving the visualization of Landsat7 ETM+ imagery. This paper introduces four remote image fusion algorithms including the Smoothing Filter Based Intensity Modulation (SFIM), High Pass Filter (HPF) Transform, Brovey Transform, and Multiplication (MLT) Transform. The effectiveness of the four remote image fusion algorithms is evaluated based on different quantitative indexes, including mean, deviation, information entropy, average gradient and correlation. The study reveals that the SFIM transform is the best method to remain spectral information of the original remote image, which does not cause spectral distortion and has highest spatial frequency information. Moreover, the fused remote images from the same sensor system are of high quality and can be used for improving the latter visual interpretation.

Highlights

With the rapid development of information technology, sensor technology and the wide application of different satellite sensors for earth observation using the visible, near infrared, shortwave infrared, thermal infrared, microwave signals, the number of remote sensing images acquired form the same region becomes increasingly huge
In order to eliminate the parameter differences existing in the remote data from different sensors, different time and image registration errors in the process of integration, some scholars have studied panchromatic and multi-spectral image fusion from multi-resolution sensor, and made some promising results
Landsat[7] was launched by the National Aeronautics and Space Bureau and carried the theme: enhanced imaging sensor (ETM+), it maintains the multi-spectral characteristics of Landsat[5] TM, the spatial resolution of thermal infrared band cover from 60m to 120m. It carries a panchromatic band with 15m spatial resolution

Summary

Introduction

With the rapid development of information technology, sensor technology and the wide application of different satellite sensors for earth observation using the visible, near infrared, shortwave infrared, thermal infrared, microwave signals, the number of remote sensing images acquired form the same region becomes increasingly huge. Effective use of massive remote sensing data from different sensors, time phase and resolution images has become a research hot spot in the field of remote image processing. In order to eliminate the parameter differences existing in the remote data from different sensors, different time and image registration errors in the process of integration, some scholars have studied panchromatic and multi-spectral image fusion from multi-resolution sensor, and made some promising results. Landsat[7] was launched by the National Aeronautics and Space Bureau and carried the theme: enhanced imaging sensor (ETM+), it maintains the multi-spectral characteristics of Landsat[5] TM, the spatial resolution of thermal infrared band cover from 60m to 120m. Researches show that if panchromatic and multi-spectral data can be effectively used, the accuracy of image interpretation, automatic classification and thematic mapping will be significantly improved

Objectives

Results

Conclusion