Date of Submission
6-15-2026
Date of Award
6-15-2026
Institute Name (Publisher)
Indian Statistical Institute
Document Type
Master's Dissertation
Degree Name
Master of Technology
Subject Name
Computer Science
Department
Computer Vision and Pattern Recognition Unit (CVPR-Kolkata)
Supervisor
Palit, Sarbani
Abstract (Summary of the Work)
Spectral Unmixing is an important field of study nowadays which focuses on gener ating fractional abundance of each pixel into constituent materials .In this thesis we have tried to unmix each pixel into three end members namely glacial lake,debris and others with primarily focusing on glacial lake.We have performed various meth ods of linear spectral unmixing and non linear spectral unmixing. These methods are applied on the collected LandSat Data of east Himalayan terrain .Experimental results demonstrate the effectiveness of the proposed approach in achieving high accuracy and efficiency in glacier lake tracking on LandSat data.
Control Number
CS2413
DOI
https://dspace.isical.ac.in/items/d308b290-0344-438f-88ce-56296b656fa7
DSpace Identifier
http://hdl.handle.net/10263/7760
Recommended Citation
Dhar, Debashis, "Spectral Unmixing using Machine Learning" (2026). Master’s Dissertations. 469.
https://digitalcommons.isical.ac.in/masters-dissertations/469