Analyzing target detection performance with multispectral fused images

Abstract

With the advance in multispectral imaging, the use of image fusion has emerged as a new and important research area. Many studies have considered the advantages of specific fusion methods over the individual input bands in terms of human performance, yet few comparison studies have been conducted to determine which fusion method is preferable to another. This paper examines four different fusion methods, and compares human performance of observers viewing fused images in a target detection task. In the presented experiment, we implemented an approach that has not been generally used in the context of image fusion evaluation: we used the paired comparison technique to qualitatively assess and scale the subjective value of the fusion methods. Results indicated that the false color and average methods showed the best results.

Saliency and Gist Features for Target Detection in Satellite Images

“…For example, for hyper-spectral satellite images, the features applied usually take advantage of the reflection characteristics of different materials [20]- [22] while for multispectral images, the features are usually extracted from fused spectra [23], [24]. However, the images discussed in this paper focus on the visible spectrum and, thus, the detection methods discussed in the previous paragraph are usually adopted.…”