Very high-resolution satellite image segmentation using variable-length multi-objective genetic clustering for multi-class change detection.
Ramen PalSomnath MukhopadhyayDebasish ChakrabortyPonnuthurai Nagaratnam SuganthanPublished in: J. King Saud Univ. Comput. Inf. Sci. (2022)
Keyphrases
- multi class
- change detection
- variable length
- multi objective
- remote sensing
- image segmentation
- fixed length
- remotely sensed
- remote sensing images
- genetic algorithm
- image analysis
- image processing
- pairwise
- evolutionary algorithm
- image registration
- satellite images
- multi class classification
- land cover
- support vector machine
- n gram
- multispectral
- remotely sensed data
- feature selection
- bitstream
- object detection
- data streams
- multi class classifier
- graph cuts
- computer vision
- remote sensing data
- unsupervised learning
- high resolution
- spatio temporal
- multiscale
- multiple classes
- human body
- concept drift
- expectation maximization
- information extraction
- image data
- objective function
- probabilistic relaxation
- decision trees