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...

With the introduction of new satellites for earth monitoring characterized by very high resolution (VHR) sensors, new algorithms to recognize shadow in the supplied images are necessary. Automatic shadow detection can enhance the interpretability of the images in several applications such as classification and change detection. Several approaches are present in literature for shadow detection a...

Usage of multispectral satellite imaging data opens vast possibilities for monitoring and quantitatively assessing properties or objects interest on a global scale. Machine learning computer vision (CV) approaches show themselves as promising tools automatizing image analysis. However, there are limitations in using CV data. Mainly, the crucial one is amount available model training. This paper...

structural analysis of remotely sensed data provides a method of assessing the structural significance of large-magnitude regional metallogenesis in the kerman porphyry cu belt in the southern part of the central iranian volcanic belt. the role of large-magnitude ring structures in the distribution of hydrothermal alteration zones and porphyry copper deposits in the southern part of the kerman ...

The purpose of multispectral satellite imagery preprocessing for Land Cover Classification is creation of enhanced satellite images before further processing and imagery analysis with final land classification and automated linear object and area border detection for selected classes of objects.

This paper extends the use of stochastic watershed, recently introduced by Angulo and Jeulin [1], to unsupervised segmentation of multispectral images. Several probability density functions (pdf), derived from Monte Carlo simulations (M realizations of N rsandom markers), are used as a gradient for segmentation: a weighted marginal pdf a vectorial pdf and a probabilistic gradient. These gradien...

A new technique for denoising and compression of multispectral satellite images to remove the effect of noise on the compression process is presented. One type of multispectral images has been considered: Landsat Enhanced Thematic Mapper Plus. The discrete wavelet transform (DWT), the dual-tree DWT, and a simple Huffman coder are used in the compression process. Simulation results show that the...