Image classification is the correctly identifying the objects of an image. Remote sensing image classification is the efficient execution of image categorization of high resolution spatial images for large remote sensing archives. High performance of image categorization known as classification is directly based upon efficient image feature extraction. As information technology and digital devices have advanced billions of individuals are now utilizing the Internet. The volume of digital data in the form of pictures, videos and text grows tremendously every day. One of the biggest concerns is keeping up with the huge online information repositories. Our daily applications are significantly dependent on multimedia content archives on the internet. The digital format is used to store images in web repositories. It can be challenging to find relevant images in the vast multimedia archive. The Remote Sensing Image Retrieval System (RSIR) searches digital images from various remote sensing archives. The user obtains the most relevant and related images from the database based on the attributes of the query image. RSIR has advanced with the development of novel techniques including transfer learning employing pre-trained models and deep learning breakthroughs. Two processes are involved in the Content-Based Image Retrieval System: feature extraction and feature matching. The goal of feature extraction is to reduce the amount of information that describes the total image content using an appropriate distance measure. Feature matching compares the features that were extracted from the database with those that were extracted from the query image. Every database-indexed image is ranked based on how far away it is from the query image. This research goes beyond remote sensing alone. Content Based Image Retrieval System Content Based Image Retrieval (CBIR) could be very useful in forestry, agriculture and geosciences where satellites can acquire images to determine the earth’s geological characteristics at a certain location and time. The fields of oceanography, geology, archaeology and astrology are other application areas for the content based image retrieval system.
Nisha Gupta (Sat,) studied this question.