Soft Computing Techniques for Change Detection in remotely sensed images : A Review
It provides a comprehensive overview for researchers in remote sensing, but is incremental as it synthesizes prior work without introducing new methods.
This paper reviews existing methods and classifications for change detection in remotely sensed images, focusing on the popular use of soft computing techniques and their learning-based classifications.
With the advent of remote sensing satellites, a huge repository of remotely sensed images is available. Change detection in remotely sensed images has been an active research area as it helps us understand the transitions that are taking place on the Earths surface. This paper discusses the methods and their classifications proposed by various researchers for change detection. Since use of soft computing based techniques are now very popular among research community, this paper also presents a classification based on learning techniques used in soft-computing methods for change detection.