This paper focuses on fusion of optical and Synthetic Aperture Radar (SAR) images to combine these two types of remotely sensed imagery for features enhancement. We have proposed a new fusion technique, namely Block-based Synthetic Variable Ratio (Block-SVR), which is based on block multiple linear regression to fuse optical and SAR imagery. In order to investigate the effectiveness, the fusion...

Remote sensing is a promising technology that finds as diverse applications as defence, urbanplanning, healthcare, and environmental management. Collecting countrywide statistics of cropyield is one of the main tasks of remote sensing. Acquiring and processing very high-resolution(VHR) satellite images are means accomplishing this task. Processing these remotely sensed(RS) image...

Texture as a measure of spatial features has been useful as supplementary information to improve image classification in many areas of research fields. This study focuses on assessing the ability of different textural vectors and their combinations to aid spectral features in the classification of silicate rocks. Texture images were calculated from Landsat 8 imagery using a fractal dimension me...

This paper focuses on the retrieval of complex images based on their textural content. We use GMRF for texture discrimination and a region-growing algorithm for texture segmentation. Relevance feedback is introduced to improve retrieval accuracy.

The technique of searching in content-based image retrieval has been actively studied in recent years. However, this technique cannot give user an overview of the database. In this paper, we propose a browsing technique using Kohonen’s Self-Organizing Map to retrieve general color image database effectively. Both chromatic and textural feature of images are analyzed to represent the content of ...

The coefficients of a weighted summation of red, green and blue intensities are shown to effect textural characteristics. Thus multispectral images can be mutated into forms that facilitate their discrimination by a given set of statistical texture measures.