Cheat-sheetChapter 8: Feature extraction
- 8.1.1. perClass feature extraction
- 8.1.2. Feature extraction domains
- 8.1.2.1. Extract features in local image neighborhoods
- 8.1.2.2. Representing objects identified in an image
- 8.1.2.3. Representing a band in spectral data
- 8.1.2.4. Transform color space
8.2 Feature extraction in local image regions
- 8.2.1. Introduction
- 8.2.2. Quick example
- 8.2.3. Region feature types
- 8.2.3.1. Raw neighborhood values
- 8.2.3.2. Local mean and standard deviation
- 8.2.3.3. Local histograms
- 8.2.3.4. Features extracted from local histograms
- 8.2.3.5. Co-occurrence matrices
- 8.2.3.6. Gaussian filter and its derivatives
- 8.2.3.7. Sobel filter
- 8.2.3.8. User-defined filter bank
- 8.2.3.9. Leung-Malik multi-orientation/multi-scale filter bank
- 8.2.3.10. Schmid rotationally-invariant filter bank
- 8.2.3.11. Maximum Response filter bank combining multiple orientations
- 8.2.3.12. Maximum Response filter bank combining multiple orientations and scales
- 8.2.3.13. Gray-level morphology features
- 8.2.3.14. User-defined feature extractors
- 8.2.4. Grid definition
- 8.2.5. Visualization of feature images computed on a grid
- 8.2.6. Computing features based on foreground mask
- 8.2.7. Propagating image labels
- 8.2.8. Visualizing regions in original image
8.3 Describe objects identified in an image
- 8.3.1. Introduction
- 8.3.2. Quick example of the entire process
- 8.3.2.1. Preparing pixel classifier
- 8.3.2.2. Applying pixel classifier
- 8.3.2.3. Segmenting objects
- 8.3.2.4. Extracting object features
- 8.3.3. Object features
- 8.3.3.1. Object size
- 8.3.3.2. Mean of object pixels
- 8.3.3.3. Sum of object pixels
- 8.3.3.4. Histogram of a specific input feature per object
- 8.3.3.5. Shape features on object mask
- 8.3.3.6. Shape features on object content
- 8.3.3.7. Example of computing per-object histogram of local gradient
- 8.3.4. Copying labels into object data set
- 8.3.5. Bounding box of objects
8.4 Feature extraction for spectral data
- 8.4.1. Introduction
- 8.4.2. Quick example
- 8.4.3. Spectral pre-processing
- 8.4.3.1. Computation of spectral indices
- 8.4.4. perClass band extractors
- 8.4.5. Examples
- 8.4.5.1. Define bands by clustering
- 8.4.5.2. Defining band extraction pipeline
- 8.4.5.3. Display band information
- 8.4.5.4. LDA spectral feature extractor
- 8.4.5.5. Defining bands manually