imageQT: Performs an image quadtree decomposition.
Description
The quadtree decomposition is achieved by recursively splitting subimages into regions of stationarity.
Usage
imageQT(image, test = TOS2D, minsize = 64,alpha=0.05, ...)
Arguments
image
An image to be decomposed.
test
A function for assessing regions of spatial homogeneity, for example TOS2D.
minsize
The smallest region to test for homogeneity.
alpha
The significance level for the homogeneity test test.
…
Any other (optional) arguments to TOS2D.
Value
An object of class imageQT with the following components:
data.name
The image analysed.
indl
The index representation of the nonstationary images in the quadtree decomposition.
resl
The results of the stationarity testing (from binfun) during the quadtree decomposition. The results giving 0 match those contained in the indl component and the results giving 1 match those contained in the indS component.
imsize
The original image dimension.
imS
The stationary subimages in the quadtree decomposition.
indS
The index representation of the stationary images in the quadtree decomposition.
minsize
The minimum testing region used during the quadtree decomposition.
Details
This function works by assessing an image for homogeneity. If it is not homogeneous, the image is split into its four subquadrants. Each of these is then tested for homogeneity. The heterogeneous subimages are then again subdivided and tested again. This procedure is repeated until either all subimages are deemed stationary or the minimum testing size minsize is reached.
References
Sonka, M., Boyle, R., and Hlavic, V. (1999) Image processing, analysis and machine vision. 2nd Edition, PWS Publishing.
Taylor, S.L., Eckley, I.A., and Nunes, M.A. (2014) A Test of Stationarity for Textured Images. Technometrics, 56 (3), 291-301.