Table of G0I stochastic distances between two image regions

Fits the \(\mathcal{G}_I^0\) law to each intensity channel of two rectangular regions of an image and computes all the stochastic distances of distancesg0i() between them.

Usage

distancesg0itable(image, marks1, marks2, p = 1/2, L = NULL)

Arguments

image: A SARImage or an array (nrow x ncol x layers).
marks1, marks2: Region limits as c(left, right, up, down), i.e. first and last column, first and last row.
p: Order of the Rényi distance.
L: Known number of looks; estimated when NULL.

Value

An object of class distancesg0itable with the marks and the table of distances (distancestable, channels in rows).

Examples

# \donttest{
res <- distancesg0itable(SanFrancisco150, c(10, 30, 10, 30),
                         c(10, 30, 120, 140), L = 4)
res
#> 
#> G0I distances table
#> 
#>           KL    Renyi Bhattacharyya Hellinger Arithmetic-Geometric Triangular
#> HH 11.385316 4.271043     2.1355217 0.8818171             5.047965   1.895534
#> HV 37.876250 8.330567     4.1652833 0.9844747            18.248424   1.993597
#> VV  3.211437 1.179735     0.5898677 0.4455994             1.239628   1.178514
#>    Harmonic-Mean
#> HH     2.9520368
#> HV     5.7440612
#> VV     0.8897873
# }