A Survey on Hyperspectral Image Classification and Object Detection Techniques

Abstract

Machine Learning is vast field which finds its application in almost every field. The image classification is one of the important application of Supervised Machine learning algorithms. Image classification is basically concerned with identifying the objects in the images. The complexity of this task is dependent on the image features and type of images. For the research work here, the hyperspectral images are considered for deep learning based image classification. The object detection in the Hyperspectral images have applications in various areas including defense, precision agriculture, atmospheric analysis, environmental analysis, anomaly detection, fraud detection , etc. The work presented here is divided into broad survey of image classification methods using machine learning and deep learning methods. Continuing with this work, the further work presents object detection methods in ML and DL. The later work presents the deep review of the research articles over Hyperspectral image classification using Machine Learning and Deep Learning Algorithms. A lot of challenges are present to solve the object detection problems in Hyperspectral images. The later section of this work describes the object detection based on Hyperspectral images survey in detail highlighting the major developments.