The senior research project that was completed was a study in the field of remote sensing and research area of image fusion technique development. Image fusion is sometimes referenced as image merging in the literature on the subject. The image fusion techniques that were developed for the project were implemented using digital image processing methods. An image fusion algorithm with two main p...

This paper reviews the recently developed processing techniques for remotely sensed imagery, including very high resolution (VHR) information extraction, super resolution techniques, hyperspectral image processing and object detection, and also some artificial intelligence approaches.

In this study, a 1-D Convolutional Neural Network (CNN) architecture was developed, trained and utilized to classify single (summer) and three seasons (spring, summer, fall) of hyperspectral imagery over the San Francisco Bay Area, California for the year 2015. For comparison, the Random Forests (RF) and Support Vector Machine (SVM) classifiers were trained and tested with the same data. In ord...

Many applications of remote sensing – like, for example, urban monitoring – require high resolution data for a correct determination of object geometry. These spatial high resolution image data contain often limited spectral information (e.g. three band RGB orthophotos). This poor spectral information lead often to classification errors between visible similar classes like water, dark pavements...

Hyperspectral remote sensing imagery contains rich information on spectral and spatial distributions of distinct surface materials. Owing to its numerous and continuous spectral bands, hyperspectral data enables more accurate and reliable material classification than using panchromatic or multispectral imagery. However, high-dimensional spectral features and limited number of available training...

Anomaly detection is one of the most important applications for hyperspectral imagery. However, some technical difficulties haven’t been effectively solved so far, such as high data dimensionality and high-order correlation between spectral bands. In this paper, a new curvelet-based image fusion algorithm is proposed for effective anomaly detection in hyperspectral imagery. In the proposed algo...