8.1 Introduction

• 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

This chapter describes feature extraction for image and spectral measurements.