Target Detection by Optimizing Anomaly Detection in Hyperspectral Image Processing using AI/ML

Category: Hardware
Organization: National Technical Research Organisation (NTRO)

Abstract

This project aims to develop Anomaly Detection Models for Hyperspectral Image Processing using AI/ML. The focus will be on optimizing deep learning models to identify targets and anomalies in hyperspectral data, which is critical for environmental monitoring and resource management.

Key Components

• Data Preprocessing: Implement techniques for data correction, de-noising, and calibration to enhance image quality.
• AI/ML Models: Use deep learning models for anomaly detection, ensuring high spectral clarity and accurate target identification.
• Target Detection Methodology: Develop a methodology for identifying and classifying targets of interest based on spectral signatures

Expected Outcome

The models will improve the accuracy and efficiency of hyperspectral image analysis, aiding in environmental monitoring and management.