期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2012
卷号：3
期号：6
页码：5447-5453
出版社：TechScience Publications
摘要：Image fusion is a formal framework for combining and utilizing data originating from different sources. It aims at producing high resolution multispectral images from a high-resolution panchromatic (PAN) image and low-resolution multispectral (MS) image. This fused image must contain more interpretable information than can be gained by using the original image. Ideally the fused image should not distort the spectral characteristics of multispectral data as well as, it should retain the basic colour content of the original data. There are many data fusion techniques that can be used which include Principal Component Analysis (PCA), Brovey Transform (BT), Multiplicative Transform (MT) and Discrete Wavelet Transform (DWT). One of the major problems associated with a data fusion technique is how to assess the quality of the fused (spatially enhanced) MS image. This paper presents a comprehensive analysis and evaluation of the most commonly used data fusion techniques. The performance of each data fusion technique is analyzed in both qualitatively and quantitatively. Then, the methods are ranked according to the conclusions drawn from visual analysis and the experimental quantitative results. To study this, a Graphical User Interface (GUI) is developed using MATLAB for image fusion to make the research outcomes available to the end user for commercial and economical activities. Due to the demand for higher classification accuracy and the need in enhanced positioning precision, there is always a need to improve the spectral and spatial resolution of remotely sensed imagery. These requirements can be fulfilled by the utilization of image data fusion techniques in classification problems at a significantly lower expense.
关键词：Image fusion is a formal framework for combining;and utilizing data originating from different sources. It aims;at producing high resolution multispectral images from a;high-resolution panchromatic (PAN) image and low-resolution;multispectral (MS) image. This fused image must contain;more interpretable information than can be gained by using;the original image. Ideally the fused image should not distort;the spectral characteristics of multispectral data as well as; it;should retain the basic colour content of the original data.;There are many data fusion techniques that can be used which;include Principal Component Analysis (PCA); Brovey;Transform (BT); Multiplicative Transform (MT) and Discrete;Wavelet Transform (DWT). One of the major problems;associated with a data fusion technique is how to assess the;quality of the fused (spatially enhanced) MS image. This;paper presents a comprehensive analysis and evaluation of the;most commonly used data fusion techniques. The performance;of each data fusion technique is analyzed in both qualitatively;and quantitatively. Then; the methods are ranked according;to the conclusions drawn from visual analysis and the;experimental quantitative results. To study this; a Graphical;User Interface (GUI) is developed using MATLAB for image;fusion to make the research outcomes available to the end user;for commercial and economical activities. Due to the demand;for higher classification accuracy and the need in enhanced;positioning precision; there is always a need to improve the;spectral and spatial resolution of remotely sensed imagery.;These requirements can be fulfilled by the utilization of image;data fusion techniques in classification problems at a;significantly lower expense.
