Abstract
Visual experience is the main way humans communicate with each other. It is one of the main ways of interacting with our society, of obtaining and transmitting ideas, of molding projects and proof of various events and phenomena. Compressing images will always remain a research challenge, given the large amounts of information we produce in images and given the large number of devices prepared to capture them daily. Multispectral and hyperspectral image compression has received considerable interest in recent years, given the increase in image capture systems and the high resolution that imagers can easily capture, thus obtaining images with a lot of highly correlated data. The development of new areas of interest in the exploration of images also brought new contributions to the research, such as: autonomous vehicles, precision agriculture, space images, satellites communication and the medical field. This process generates very large images, which create other problems, their transmission, storage and computational power for the analysis of the data obtained. With that scenario, digital image compression has become a major factor in the operation of many day-to-day technologies. In this article, we address the issue of multispectral image compression and the algorithms used in this process.
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