Combining of Markov Random Field and Convolutional Neural Networks for Hyper/Multispectral Image Classification.
Halil Mertkan SahinBruce GrieveHujun YinPublished in: IDEAL (2023)
Keyphrases
- markov random field
- multispectral
- image classification
- convolutional neural networks
- remote sensing
- remote sensing images
- remotely sensed data
- belief propagation
- higher order
- graph cuts
- multispectral images
- mrf model
- image data
- image segmentation
- parameter estimation
- pairwise
- random fields
- satellite images
- energy function
- spatial resolution
- maximum a posteriori
- multispectral satellite images
- remote sensing data
- feature extraction
- image representation
- image analysis
- hyperspectral
- high spatial resolution
- land cover
- prior model
- machine learning
- image features
- potential functions
- change detection
- sparse representation
- similarity measure
- mrf models
- frame rate
- image processing
- bayesian framework