Change Detection and Image Time Series Analysis 1 presents a wide
range of unsupervised methods for temporal evolution analysis
through the use of image time series associated with optical and/or
synthetic aperture radar acquisition modalities. Chapter 1
introduces two unsupervised approaches to multiple-change detection
in bi-temporal multivariate images, with Chapters 2 and 3
addressing change detection in image time series in the context of
the statistical analysis of covariance matrices. Chapter 4 focuses
on wavelets and convolutional-neural filters for feature extraction
and entropy-based anomaly detection, and Chapter 5 deals with a
number of metrics such as cross correlation ratios and the
Hausdorff distance for variational analysis of the state of snow.
Chapter 6 presents a fractional dynamic stochastic field model for
spatio temporal forecasting and for monitoring fast-moving
meteorological events such as cyclones. Chapter 7 proposes an
analysis based on characteristic points for texture modeling, in
the context of graph theory, and Chapter 8 focuses on detecting new
land cover types by classification-based change detection or
feature/pixel based change detection. Chapter 9 focuses on the
modeling of classes in the difference image and derives a
multiclass model for this difference image in the context of change
vector analysis.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
