wave.variance.2d {waveslim}

Wavelet Analysis of Images

Description

Produces an estimate of the multiscale variance with approximate confidence intervals using the 2D MODWT.

Usage

wave.variance.2d(x, p = 0.025)

Arguments

x

image

p

(one minus the) two-sided p-value for the confidence interval

Details

The wavelet variance is basically the average of the squared wavelet coefficients across each scale and direction of an image. As shown in Mondal and Percival (2012), the wavelet variance is a scale-by-scale decomposition of the variance for a stationary spatial process, and certain non-stationary spatial processes.

Value

Data frame with 3J+1 rows.

Author(s)

B. Whitcher

References

Mondal, D. and D. B. Percival (2012). Wavelet variance analysis for random fields on a regular lattice. IEEE Transactions on Image Processing 21, 537–549.