cloud_fill: Cloud fill using the algorithm developed by Xiaolin Zhu

In azvoleff/teamlucc: TEAM land use and cover change data processing toolkit

Description

This function is called by the cloud_remove function. It is not intended to be used directly.

Usage

cloud_fill(cloudy, clear, cloud_mask, dims, num_class, min_pixel, max_pixel,
  cloud_nbh, DN_min, DN_max, verbose = FALSE)

Arguments

cloudy	the cloudy image as a matrix, with pixels in columns (in column-major order) and with number of columns equal to number of bands
clear	the clear image as a matrix, with pixels in columns (in column-major order) and with number of columns equal to number of bands
cloud_mask	the cloud mask image as a vector (in column-major order), with clouds coded with unique integer codes starting at 1, and with areas that are clear in both images coded as 0. Areas that are missing in the clear image, should be coded as -1.
dims	the dimensions of the cloudy image as a length 3 vector: (rows, columns, bands)
num_class	set the estimated number of classes in image
min_pixel	the sample size of similar pixels
max_pixel	the maximum sample size to search for similar pixels
cloud_nbh	the range of cloud neighborhood (in pixels)
DN_min	the minimum valid DN value
DN_max	the maximum valid DN value
verbose	whether to print detailed status messages

Value

array with cloud filled image with dims: cols, rows, bands parameter, containing the selected textures measures

References

Zhu, X., Gao, F., Liu, D., Chen, J., 2012. A modified neighborhood similar pixel interpolator approach for removing thick clouds in Landsat images. Geoscience and Remote Sensing Letters, IEEE 9, 521–525.

azvoleff/teamlucc documentation built on May 11, 2019, 5:19 p.m.