Hyperspectral Image Acquisition Methods and Processing Techniques Based on Traditional and Deep Learning Methodologies-A Study

Hyperspectral image processing is a very rapidly growing technology these days. It extends the scope of its applications across diversified fields such as Remote sensing, precision agriculture, medicine, Computer Vision applications and many more. Especially Hyperspectral Imagery, benefiting from its very own nature of providing rich spectral information, find many apllications in the field of Remote sensing and Earth observation. With the development of hyperspectral imaging sensor technology, the supply of HSI data has increased greatly, creating a need for proportionate rise in the HIS Processing techniques for better interpretation of data. In this context Deep Learning has become a viable option to handle huge datasets like Hyperspectral Imagery. Thus many enthusiastic researchers are showing interest in the domain of Hyperspectral Image Processing. This paper attempts to provide the basic concepts of HSI acquisition and processing at an abstract level with more focus given to Deep Learning based HSI processing tasks. So that the work will come in handy to the beginners in this field to get the preliminary concepts of HSI at a glance. To the best of our knowledge this work is first of its kind to bring to together in this study the the concepts of HSI acquisition and HSI processing.