Journal: Current Medical Imaging
Guest editor(s):Dr. Fadi Al-Turjman

Introduction

Multispectral and hyperspectral imaging is an interdisciplinary research area, widely focuses on spectral, spatial, and temporal data. It offers a plethora of opportunities to efficiently analyze the vast area of the earth's surface. However, there are numerous factors such as dimensionality and size of the hyperspectral data, lesser training samples, scattering of light during data acquisition processes, varied pixels, and various geometric and atmospheric distortions makes the data to be inherently complex and challenging to handle. These instances create potential challenges over the existing methodologies in an efficient analysis and processing of the data sets. Hence, to effectively address these concerns, researchers worldwide have started focusing on finding innovative and efficient methodologies to store and process huge amounts of hyperspectral and multispectral data. Intelligent information retrieval is an emerging technique that replaces machines with humans. It makes use of intelligent technologies such as artificial intelligence and machine learning to schedule, plan, process, store, extract and interpret the text to support the decision making process with improved accuracy and performance measures. Thus, intelligent information retrieval implemented in the context of multispectral and hyperspectral imaging improves the better-preprocessing process and extracts more knowledge from the data. Further, it is the most critical technology that can significantly enhance hyperspectral and multispectral imaging applications if implemented in an appropriate way. This special issue, entitled "Intelligent information retrieval for multispectral and hyperspectral imaging," provides a comprehensive platform for the researchers to present novel and innovative solutions against this background. The major objective of this special issue is to advance the utility and capability of the hyperspectral and multispectral imaging algorithms with intelligent information retrieval techniques to address the needs of current and emerging applications potentially and to explore comprehensive insights against this research field. We welcome the researchers to exchange information and innovative ideas against the community of spectral data analysts, developers, geospatial researchers, and application domain experts. Papers are solicited explicitly to topics related to spectral imaging and intelligent information retrieval systems.

Keywords

Multispectral and hyperspectral imaging, Internet of Things (IoT), Intelligent imaging, Artificial Intelligence (AI), Machine learning (ML), Cloud/Edge Computing