In this paper we propose a novel algorithm for the pansharpening of multispectral images based on the use of a Total Variation (TV) image prior. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images, and uses the sensor characteristics to model the observation process of both panchromatic and multispectral ...

A new algorithm based on the fusion of edge and multispectral information is proposed for the pixel-wise classification of very high-resolution (VHR) remotely sensed imagery. It integrates the multispectral, spatial and structural information existing in the image. The edge feature is first extracted using an improved multispectral edge detection method, which takes into account the original mu...

We apply a general form of affine transformation model to compensate illumination variations in a series of multispectral images of a static scene and compare it to a particular affine and a diagonal transformation models. These models operate in the original multispectral space or in a lower-dimensional space obtained by Singular Value Decomposition (SVD) of the set of images. We use a system ...

In this theoretical paper we address the question of how to encode the local signal variation of multidimensional, multispectral signals. To this end, we first extend the concept of intrinsic dimension to the case of multispectral images in a way which is not depending upon the chosen colour space. We then show how additive, multiplicative, and occluded superpositions of oriented layers can be ...

In this paper we present a super resolution Bayesian methodology for pansharpening of multispectral images. By following the hierarchical Bayesian framework, and by applying variational methods to approximate probability distributions this methodology is able to: (a) incorporate prior knowledge on the expected characteristics of the multispectral images, (b) use the sensor characteristics to mo...

Due to the high spatial resolution requirements especially 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, Ultracam), however, chal...

This dissertation addresses the advantage of using multispectral narrow-band images over conventional broad-band images for improved face recognition under varying illumination. To verify the effectiveness of multispectral images for improving face recognition performance, three sequential procedures are taken into action: multispectral face image acquisition, image fusion for multispectral and...

Most of the satellite sensors, presently operating in the optical domain, are providing a data set comprising multispectral images at a low spatial resolution and images at a higher spatial resolution but with a lower spectral content. The trend of satellite sensors is similar to the present situation. The idea of fusing multispectral images with a highest spatial resolution enables the creatio...