A new multispectral image context classification, which is based on a stochastic relaxation algorithm and Markov-Gibbs random field, is presented. The implementation of the relaxation algorithm is related to a form of optimization programming using annealing. The authors motivate a Bayesian context decision rule, and a Markov-Gibbs model for the original Landsat MSS (multispectral scanner) imag...

Traditional multispectral classification based road extraction methods separate roads from other ground features according to spectral characteristics of individual pixels. To take use of the spatial properties of high-resolution satellite images, in this paper we integrate spectral information from the multispectral (MS) image with spatial information from the panchromatic (Pan) image for road...

Multispectral images usually present complimentary information such as visual-band imagery and infrared imagery (near infrared or long wave infrared). There are strong evidences that the fused multispectral imagery (in gray scales) increases the reliability of interpretation (Rogers & Wood, 1990; Essock et al., 2001) and thus good for machine analysis (computer vision); whereas the colorized mu...

Remote sensing data provides much essential and critical information for monitoring many applications such as image fusion, change detection and land cover classification. This paper proposed about the classification and extraction of spatial features in urban areas for high resolution multispectral satellite image. Spectral information is the foundation of remotely sensed image classification....

Abstract— The combined image fusion method which proposed in this paper integrates the information from multiple fusion algorithms which is more suitable for human visual perception. Multispectral images (SPOT) have low spatial resolution. So, integrating of low-resolution multispectral and high-resolution panchromatic (IKONOS) images is a technique for improving the spatial quality of multispe...

Image fusion is a method for obtaining a highly informative image by merging the relative information of an object obtained from two or more image sources of the same scene. The satellite cameras give a single band panchromatic (PAN) image with high spatial information and multispectral (MS) image with more spectral information. The problem exists today is either PAN or MS image is available fr...

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...