Hybrid optimal joint spatial-spectral hyperspectral image classification using modified DHO-based GIF with JRKNN

ABSTRACT

Hyperspectral images (HSI) have been extensively utilized in environmental protection, agriculture, and land cover applications. But, it is difficult to classify due to improper exploitation of spatial and spectral features. As a result, this paper proposes a unified guided image filtering (GIF) method that uses a joint representation model of the K-nearest neighbour algorithm (JRKNN) to extract spatial context information and preserve edges while denoising classification results. In addition, a new meta-heuristic optimization algorithm called modified deer hunting optimization (MDHO) is implemented to minimize the cost function in GIF by optimizing the regularization parameter and edge-aware weighting, which is named GIF-MDHO. Finally, the simulation results show that the GIF-MDHO with JRKNN approach performed superior as compared to the existing support vector machine (SVM) by KNN and even the KNN-GIF methods with an improved accuracy of 1.02%, precision, recall , and F1-score of 0.78%, 0.91%, and 0.74%, respectively.

KEYWORDS:

• Hyperspectral imaging
• hyperspectral image classification
• k-nearest neighbour
• guided image filtering
• deer hunting optimization

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

M. Krishna Satya Varma

M. Krishna Satya Varma, Research Scholar, Annamalai University, Chidambaram, completed his graduation in Information Technology in D V R college of Engineering and Technology affiliated to JNTU Hyderabad, and the master’s degree in information technology SRKREC affiliated to Andhra University. He has 11 years of experience in teaching. His area of interest includes Image processing, Data Mining, Machine Learning.

K. Raja

Dr. K. Raja, presently working as Assistant Professor in Department of Information Technology, Annamalai University, Chidambaram. He has 16 years of experience in teaching. His interested research area is Computer Graphics, Computer Networks, Multimedia. He published 18 research papers and presently guiding 4 research scholars.

N. K. Kameswara Rao

Dr. N. K. Kameswara Rao, presently working as Associate Professor in Department of Computer Science and Engineering, S R K R Engineering College, Bhimavaram. He has 19 years of experience in teaching and 4 years in industry. His interested research area is Image processing, Data Mining, Machine Learning. He published 24 research papers and presently guiding 1 research scholar.