In this paper we present an automated method for classifying astronomical objects in multispectral wide-field images. The method is divided into three main tasks. The first one consists of locating and matching the objects in the multispectral images. In the second task we create a new representation for each astronomical object using its multispectral images, and also we find a set of features...

Panchromatic and multispectral images are useful for the acquisition of geospatial information about the Earth surface for the assessment of land resources and environment monitoring. Panchromatic images usually have a better spatial resolution than the multispectral ones of the same sensor, while the multispectral images provide spectral properties of the objects. Image fusion methods are need...

Multispectral images are composed of a series of images at differing optical wavelengths. Since these images can be quite large, they invite efficient 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. The authors...

This paper presents a novel technique, namely texture-guided multisensor superresolution (TGMS), for fusing a pair of multisensor multiresolution images to enhance the spatial resolution of a lower-resolution data source. TGMS is based on multiresolution analysis, taking object structures and image textures in the higher-resolution image into consideration. TGMS is designed to be robust against...

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...

Compression of multispectral images (obtained from sensors that sample in both the spatial and the spectral domains) is important for reducing the transmission and storage requirements of such data. This article describes versatile software developed to simulate a family of compression algorithms. Two algorithms are selected as the most suitable for implementation. The first is a moderately hig...

Hybrid-resolution multispectral imaging is a framework to acquire multispectral images through a reconstruction procedure using two types of measurement data with different spatial and spectral resolutions. In this paper, we propose a new method for such a framework on the basis of a full-resolution RGB image and the data obtained from an image sensor with a multispectral filter array (MSFA). I...

An attempt has been made in this paper to classify multispectral images using customized particle swam optimization. To reduce the time consumption due to increase in dimensionality of multispectral imagery a preprocessing is done using feature extraction based on decision boundary. The customized particle swam optimization then works on the reduced multispectral imagery to find globally optima...

We present here a method that makes use of multispectral image data and generates a novel “photometric-invariant multispectral image” for this type of data. For RGB, an invariant image has been constructed independent of the colour and intensity of the illuminant and of shading. To generate this image either a set of calibration images is required, or entropy information taken from a single ima...

Multispectral Iris Recognition Analysis: Techniques and Evaluation by Christopher K. Boyce Master of Science in Electrical Engineering West Virginia University Lawrence Hornak, Ph.D., Chair Arun Ross, Ph.D. (Co-chair) This thesis explores the benefits of using multispectral iris information acquired using a narrow-band multispectral imaging system. Commercial iris recognition systems typically ...