Yüksek Boyutlu Model Gösterilimi ile Hiperspektral Görüntülerde Anomali Tespiti

Hyperspectral imaging (HSI) is an important imaging technology that enables the high sensitivity and accuracy analysis of wide areas through its multispectral band structure. Anomaly detection in hyperspectral images can be defined as the detection of pixels that do not belong to the background and whose spectral properties are unknown. In this study, a method based on High Dimensional Model Representation (HDMR) is proposed for detecting anomalies in hyperspectral images. The effectiveness of the proposed method has been tested on a sample image and compared with commonly used anomaly detection methods. The HDMR-based anomaly detection algorithm has shown to be more effective in suppressing the background compared to other methods by making anomaly pixels more visible.