Image fusion, which refers to extracting and then combining the most meaningful information
from different source images, aims to generate a single image that is more informative and …

Object-based image classification for land-cover mapping purposes using remote-sensing
imagery has attracted significant attention in recent years. Numerous studies conducted over …

Reliable and accurate crop classification maps are an important data source for agricultural
monitoring and food security assessment studies. For many years, crop type classification …

Earth observation through remote sensing images allows the accurate characterization and
identification of materials on the surface from space and airborne platforms. Multiple and …

Since the publishing of the first edition of Classification Methods for Remotely Sensed Data
in 2001, the field of pattern recognition has expanded in many new directions that make use …

Aims Mapping vegetation through remotely sensed images involves various considerations,
processes and techniques. Increasing availability of remotely sensed images due to the …

In this paper, multivariate regression is adopted to improve spectral quality, without
diminishing spatial quality, in image fusion methods based on the well-established …

In this paper, we propose a general purpose, simple and fast fusion algorithm based on
guided image filter. The proposed method can well combine useful source image …

This paper introduces a novel approach for evaluating the quality of pansharpened
multispectral (MS) imagery without resorting to reference originals. Hence, evaluations are …

Image fusion can be performed on images either in spatial domain or frequency domain
methods. Frequency domain methods will be most preferred because these methods can …