This paper reports the outcomes of the 2014 Data Fusion Contest organized by the Image
Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and …

The expansion of satellite technologies makes remote sensing data abundantly available.
While the access to such data is no longer an issue, the analysis of this kind of data is still …

A new technique for the segmentation of single-and multiresolution (MR) remote sensing
images is proposed. To guarantee the preservation of details at fine scales, edge-based …

The use of Very High Spatial Resolution (VHSR) imagery in remote sensing applications is
nowadays a current practice whenever fine-scale monitoring of the earth's surface is …

Panchromatic (PAN) and multispectral (MS) imagery classification is one of the hottest topics
in the field of remote sensing. In recent years, deep learning techniques have been widely …

Missing data in very high spatial resolution (VHR) optical imagery take origin mainly from the
acquisition conditions. Their accurate reconstruction represents a great methodological …

The extraction of urban patterns from very high spatial resolution (VHSR) optical images
presents several challenges related to the size, the accuracy and the complexity of the …

The automated detection and map** of landslides from Very High Resolution (VHR)
images present several challenges related to the heterogeneity of landslide sizes, shapes …

Fuzzy C-means (FCM) clustering has been widely used in analyzing and understanding
remote sensing images. However, the conventional FCM algorithm is sensitive to …

Historical and recent developments in the field of robust clustering and their applications are
reviewed. The discussion focuses on different strategies that have been developed to …