panSharp: Pan sharpen low resolution satellite channels by using the...

In environmentalinformatics-marburg/satelliteTools: What the package does (short line)

Description

The function PAN sharpens the low resolution channels with the panchromatic channel. This is done by multiplying the normlized XS channel with the PAN channel (see Details).

Usage

## S4 method for signature 'Satellite'
panSharp(x, filter = c("mean", "Gauss", "median"),
  winsize = 1, subset = FALSE)

## S4 method for signature 'RasterStack'
panSharp(x, pan, filter = c("mean", "Gauss",
  "median"), winsize = 1)

## S4 method for signature 'RasterLayer'
panSharp(x, pan, pan_lp, filter = c("mean", "Gauss",
  "median"), winsize = 1)

Arguments

x	Satellite or raster::Raster* object.
filter	Type of filter to be used for smoothing the PAN raster; one of mean (default), Gauss, median.
winsize	Size of the filter window in x and y direction; defaults to 3.
subset	Logical; if TRUE, all layers except for the cropped ones are being dropped; if FALSE, the cropped layers are being appended to the Satellite object.
pan	A raster::RasterLayer object of the panchromatic channel
pan_lp	A raster::RasterLayer object containing a lowpass filtering of pan

Details

Pan sharpen low resolution satellite channels by using the high resolution panchromatic channel. This function uses the same algorithm as the OTB Toolbox where "The idea is to apply a low pass filter to the panchromatic band to give it a spectral content (in the Fourier domain) equivalent to the XS data. Then we normalize the XS data with this low-pass panchromatic and multiplythe result with the original panchromatic band." (see https://www.orfeo-toolbox.org/SoftwareGuide/SoftwareGuidech13.html#x41-2140011).

Value

If x is a Satellite object, a Satellite object (with added pansharpened layers); if x is a raster::Raster* object, a raster::Raster* with pansharpened layer(s).

References

Al-amri, Salem Saleh, Namdeo V. Kalyankar, and Santosh D. Khamitkar. "A comparative study of removal noise from remote sensing image." http://ijcsi.org/articles/A-Comparative-Study-of-Removal-Noise-from-Remote-Sensing-Image.php

Bhattacharya, Amit K., P. K. Srivastava, and Anil Bhagat. "A modified texture filtering technique for satellite images." Paper presented at the 22nd Asian Conference on Remote Sensing. Vol. 5. 2001. http://a-a-r-s.org/aars/proceeding/ACRS2001/Papers/DPA3-08.pdf

Randen, Trygve, and John Hakon Husoy. "Filtering for texture classification: A comparative study." Pattern Analysis and Machine Intelligence, IEEE Transactions on 21.4 (1999): 291-310. http://dx.doi.org/10.1109/34.761261.

PAN sharpening articles
- http://remotesensing.spiedigitallibrary.org/article.aspx?articleid=1726558
- http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=1368950&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D1368950

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC8*.TIF"), full.names = TRUE)
sat <- satellite(files)

## Not run: 
## using 'satellite' object
sat_ps <- panSharp(sat)

par(mfrow = c(1, 2))
plot(getSatDataLayer(sat_ps, "B002n"), main = "raw", legend = TRUE)
plot(getSatDataLayer(sat_ps, "B002n_PAN_sharpend"), 
     main = "pan-sharpened", legend = TRUE)
dev.off()

## End(Not run)      

## using 'RasterLayer' object
rst_b001n <- getSatDataLayer(sat, "B001n")
rst_panch <- getSatDataLayer(sat, getSatBCDEFromType(sat, type = "PCM"))
rst_b001n_ps <- panSharp(rst_b001n, rst_panch)

par(mfrow = c(1, 2))
plot(rst_b001n, main = "raw", legend = FALSE)
plot(rst_b001n_ps, main = "pan-sharpened", legend = FALSE)
dev.off()      

environmentalinformatics-marburg/satelliteTools documentation built on May 16, 2019, 8:16 a.m.