Change detection in hyperspectral imagery is the process of comparing two spectral images of the same scene acquired at different times, and finding a small set of pixels that has the largest apparent spectral change. We present an approach that operates in a two-dimensional space rather than in the original high-dimensional space of the images, which can be greater than 100 spectral channels. ...

Change detection by unmixing has been shown to provide enhanced change detection performance for hyperspectral images with respect to more traditional approaches, especially when the temporal images contain sub-pixel level changes. In a recent paper, change detection by spectral unmixing was investigated in detail and the advantages that can be gained by using such an approach were systematical...

In this paper, we propose a new approach to change detection that is based on the appearance or disappearance of 3D lines, which may be short, as seen in a new image. These 3D lines are estimated automatically and quickly from a set of previously-taken learning-images from arbitrary view points and under arbitrary lighting conditions. 3D change detection traditionally involves unsupervised esti...

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Target objects presented within color images of naturalistic scenes were deleted or rotated during a saccade to or from the target object or to a control region of the scene. Despite instructions to memorize the details of the scenes and to monitor for object changes, viewers frequently failed to notice the changes. However, the failure to detect change was mediated by three other important fac...

Cloud-free optical satellite imagery simplifies remote sensing, but land-cover phenology limits existing solutions to persistent cloudiness to compositing temporally resolute, spatially coarser imagery. Here, a new strategy for developing cloud-free imagery at finer resolution permits simple automatic change detection. The strategy uses regression trees to predict pixel values underneath clouds...

A video sequence usually consists of separate scenes, and each scene includes many shots. For video understanding purposes, it is most important to detect scene breaks. To analyze the content of each scene, detection of shot breaks is also required. Usually, a scene break is associated with a simultaneous change of image, motion, and audio characteristics, while a shot break is only accompanied...