In this paper, we consider a model of lossless image compression in which each band of a multispectral image is coded using a prediction function involving values from a previously coded band of the compression, and examine how the ordering of the bands affects the achievable compression. We present an efficient algorithm for computing the optimal band ordering for a multispectral image. This a...

This paper presents two multimodal prototypes for remote sensing image classification where user interaction is an important part of the system. The first one applies pansharpening techniques to fuse information from different satellite sensors to obtain a high resolution (HR) multispectral image. Once the HR image has been classified the user can interact with the system to select a class of i...

The simultaneous capture of imaging data at multiple wavelengths across the electromagnetic spectrum is highly challenging, requiring complex and costly multispectral image devices. In this study, we investigate the feasibility of simultaneous multispectral imaging using conventional image sensors with color filter arrays via a novel comprehensive framework for numerical demultiplexing of the c...

The design of a system for multispectral image capture will be influenced by the imaging application, such as image archiving, vision research, illuminant modification or improved (trichromatic) color reproduction. A key aspect of the system performance is the effect of noise, or error, when acquiring multiple color image records and processing of the data. This research provides an analysis th...

Due to the high spatial resolution requirements for urban information systems, aerial photography has been used as standard imaging input. The advent of new satellites with a resolution of better than 1m (e.g., IKONOS, Quickbird) and digital airborne scanners with excellent geometric fidelity and high spatial resolutions in the cm range (e.g., HRSC, ADS, DMC), however, challenges the analog air...

This paper focuses on the implementation of the pansharpened image fusion technique proposed in the companion paper [A Nonlocal Variational Model for Pansharpening Image Fusion, SIAM Journal on Imaging Sciences, 2014, to appear]. Pansharpening refers to the process of inferring a high resolution multispectral image from a high resolution panchromatic image and low resolution multispectral one. ...

This paper presents a novel multispectral stereo image correspondence approach. It is evaluated using a stereo rig constructed with a visible spectrum camera and a long wave infrared spectrum camera. The novelty of the proposed approach lies on the usage of Hough space as a correspondence search domain. In this way it avoids searching for correspondence in the original multispectral image domai...

Remote sensing systems designed to monitor the surface environment employ a multispectral design such as parallel sensor arrays thereby detecting radiation in a small number of broad wavelength bands in order to provide increased spectral discrimination. These broad-band multispectral systems allow discrimination of different types of vegetation, rocks and soils, clear and turbid water, and som...

Recently, sparse representation (SR) and joint sparse representation (JSR) have attracted a lot of interest in image fusion. The SR models signals by sparse linear combinations of prototype signal atoms that make a dictionary. The JSR indicates that different signals from the various sensors of the same scene form an ensemble. These signals have a common sparse component and each individual sig...

We build a dataset including four kinds of multispectral images with labeled key point correspondence. The dataset includes 7 RGB/NIR image pairs, 4 RGB/Depth image pairs, 3 Flash/no-flash image pairs and 4 different exposure image pairs. In each pair, we uniformly select corner points and label their correspondences. The resolution of the RGB/Depth image pairs is 640 × 480 and all the other im...