fusionRS: Fusion of images with different observation geometries

In ytarazona/ForesToolboxRS: Remote Sensing Tools for Forest Monitoring

Fusion of images with different observation geometries

Description

This algorithm allows to fusion images coming from different spectral sensors (e.g., optical-optical, optical and SAR, or SAR-SAR). It is also possible to obtain the contribution (%) of each variable in the fused image.

Usage

fusionRS(x, y, stand.varb = TRUE, na.rm = FALSE, verbose = FALSE)

Arguments

x	Optical image. It should be RasterStack or RasterBrick
y	Radar image. It should be RasterStack or RasterBrick
stand.varb	Logical. If TRUE, the PCA is calculated using the correlation matrix (standardized variables) instead of the covariance matrix (non-standardized variables)
na.rm	If TRUE the NA values of the images will be omitted from the analysis
verbose	This parameter is Logical. It prints progress messages during execution

Value

A list with Fused images (RasterStack), Variance, Proportion of variance, Cumulative variance, Correlation and Contribution in percentage.

Note

Before executing the function, it is recommended that images coming from different sensors or from the same sensor have a co-registration.

Examples

## Not run: 
library(ForesToolboxRS)
library(raster)

# Load example datasets
data(img_optical)
data(img_radar)

# Fusion of images - optical and radar data
fusion <- fusionRS(x = img_optical, y = img_radar, na.rm = TRUE)
plotRGB(fusion[[1]], 1, 2, 3, axes = FALSE, stretch = "lin", main = "Fused images")

## End(Not run)

ytarazona/ForesToolboxRS documentation built on Nov. 23, 2024, 6:03 p.m.