1 Multispectral images are composed of a series of images at di ering optical wavelengths. Since these images can be quite large, they invite e cient source coding schemes for reducing storage and transmission requirements. Because multispectral images include a third (spectral) dimension with nonstationary behavior, these multilayer data sets require specialized coding techniques. In this pape...

Multispectral image capture (i.e, more than three channels) facilitates both more accurate tristimulus estimation and possibilities for spectral reconstruction of each scene pixel. A seven-channel camera was assembled using approximately 50 nm bandwidth interference filters, manufactured by Melles Griot, in conjunction with a Kodak Professional DCS 200m digital camera. Multichannel images were ...

One of the practical issues in clustering is the specification of the appropriate number of clusters, which is not obvious when analyzing geospatial datasets, partly because they are huge (both in size and spatial extent) and high dimensional. In this paper we present a computationally efficient model-based split and merge clustering algorithm that incrementally finds model parameters and the n...

The Hierarchical Segmentation (HSEG) algorithm is an approach for producing high quality, hierarchically related image segmentations. The VisiMine image information mining system utilizes clustering and segmentation algorithms for reducing visual information in multispectral images to a manageable size. The project1 discussed herein seeks to enhance the VisiMine system through incorporating hie...

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We describe a method for selecting filter sets for simultaneously optimizing the classification rates in two separate spectral signature classification problems. Our system’s performance is comparable to traditional hyper-or multispectral classifiers, but uses fewer filters. c © 2010 Optical Society of America OCIS codes: (110.1758) Computational imaging, (110.4234) Multispectral and hyperspect...

Cloud is one of the most common interferers in Moderate Resolution Imaging Spectrum-radiometer (MODIS) remote sensing imagery. Because of cloud interference, much important and useful information covered by cloud cannot be recovered well. How to detect and remove cloud from MODIS imagery is an important issue for wide application of remote sensing data. In general, cloud can be roughly divided ...

In this article we describe five major classification approaches and provide a comparative analysis on a multispectral image. First we define the classification problem as following. Given a sample set of input-output pairs, the objective of supervised classification is to find a function that learns from the given input-output pairs, and predicts an output for any unseen input (but assumed to ...

Classification is a very important task for scene interpretation and other applications of multispectral images. Feature extraction is a key step for classification. By extracting more nonlinear features than corresponding number of linear features in original feature space, classification accuracy for multispectral images can be improved greatly. Therefore, in this paper, an approach based on ...