Comparative Analysis of RGB Imaging and Hyperspectral Imaging using Machine Learning Techniques

Image processing is the class of methods for face recognition, object detection, image compression, classification, etc. Hyperspectral imaging is the parallel acquisition of spatial and spectral information from an image, making it a useful tool for many applications. It is similar to an RGB color image, but it has a lot more channels and thereby making it challenging to visualize by the human eye. This paper discussed the fundamentals and components of RGB imaging and hyperspectral imaging. We also discussed the challenges of using a hyperspectral imaging system and some comparative study results of RGB imaging and hyperspectral imaging for various application areas. We also discussed the role of machine learning techniques in RGB imaging and hyperspectral image analysis. We also discussed future challenges and the scope of hyperspectral imaging. Though hyperspectral imaging has certain limitations, it can be a powerful image analysis tool for many applications in the future