cloud_fill: Cloud fill using the algorithm developed by Xiaolin Zhu

Description Usage Arguments Value References

View source: R/RcppExports.R

Description

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

Usage

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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 June 4, 2017, 12:08 a.m.