Classification of hyperspectral images by integrating spectral and spatial information
محل انتشار: پنجمین کنفرانس بین المللی محاسبات نرم
سال انتشار: 1402
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 63
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شناسه ملی سند علمی:
CSCG05_166
تاریخ نمایه سازی: 9 اردیبهشت 1403
چکیده مقاله:
Hyperspectral imaging has emerged as a prominent technology for remotely sensing and analyzing complex landscapes. However, accurately classifying hyperspectral images is a challenging task due to the high-dimensionality and inherent spectral variability. In this study, we propose a novel approach to enhance classification accuracy by integrating both spectral and spatial information. The main objective of this research is to address the limitations of traditional approaches that rely solely on spectral information for classification. To achieve this, we applied a two-step approach. First, we extracted the spectral features from the hyperspectral images using state-of-the-art algorithms. Then, we integrated spatial information by considering the contextual relationships between pixels through spatial filtering techniques. This allowed us to capture more relevant information and enhance the classification performance. This study highlights the importance of incorporating both spectral and spatial information for the accurate classification of hyperspectral images.
کلیدواژه ها:
نویسندگان
Ayda Mirzazadeh
Bachelor of Computer Engineering, Rasht Azad University;
Abdorreza Hesam Mohseni
University Lecturer of Computer Engineering, University of Guilan, Guilan, Iran;