RStoolbox: histMatch – R documentation

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histMatch

Image to Image Contrast Matching

Description

Performs image to image contrast adjustments based on histogram matching using empirical cumulative distribution functions from both images.

Usage

histMatch(x, ref, xmask = NULL, refmask = NULL, nSamples = 1e+05,
  intersectOnly = TRUE, paired = TRUE, forceInteger = FALSE,
  returnFunctions = FALSE, ...)

Arguments

`x`	Raster*. Source raster which is to be modified.
`ref`	Raster*. Reference raster, to which x will be matched.
`xmask`	RasterLayer. Mask layer for `x` to exclude pixels which might distort the histogram, i.e. are not present in `ref`. Any NA pixel in `xmask` will be ignored (`maskvalue = NA`).
`refmask`	RasterLayer. Mask layer for `ref`. Any NA pixel in `refmask` will be ignored (`maskvalue = NA`).
`nSamples`	Integer. Number of random samples from each image to build the histograms.
`intersectOnly`	Logical. If `TRUE` sampling will only take place in the overlap extent of the two rasters. Otherwise the full rasters will be used for sampling.
`paired`	Logical. If `TRUE` the corresponding pixels will be used in the overlap.
`forceInteger`	Logical. Force integer output.
`returnFunctions`	Logical. If `TRUE` the matching functions will be returned instead of applying them to `x`.
`...`	Further arguments to be passed to writeRaster.

Value

A Raster* object of x adjusted to the histogram of ref. If returnFunctions = TRUE a list of functions (one for each layer) will be returned instead.

Note

x and ref must have the same number of layers.

References

Richards and Jia: Remote Sensing Digital Image Analysis. Springer, Berlin, Heidelberg, Germany, 439pp.

Examples

library(ggplot2)
library(raster)
data(rlogo)
## Original image a (+1 to prevent log(0))
img_a <-  rlogo + 1 
## Degraded image b
img_b <- log(img_a)
## Cut-off half the image (just for better display)
img_b[, 1:50] <- NA

## Compare Images before histMatching
ggRGB(img_a,1,2,3)+
        ggRGB(img_b, 1,2,3, ggLayer = TRUE, stretch = "lin", q = 0:1) +
        geom_vline(aes(xintercept = 50))+
        ggtitle("Img_a vs. Img_b")

## Do histogram matching
img_b_matched <- histMatch(img_b, img_a)

## Compare Images after histMatching
ggRGB(img_a, 1, 2, 3)+
        ggRGB(img_b_matched, 1, 2, 3, ggLayer = TRUE, stretch = "lin", q = 0:1) +
        geom_vline(aes(xintercept = 50))+
        ggtitle("Img_a vs. Img_b_matched")

## Histogram comparison
opar <- par(mfrow = c(1, 3), no.readonly = TRUE)
img_a[,1:50] <- NA
redLayers <- stack(img_a, img_b, img_b_matched)[[c(1,4,7)]]
names(redLayers) <- c("img_a", "img_b", "img_b_matched")

hist(redLayers) 
## Reset par 
par(opar)

RStoolbox

Tools for Remote Sensing Data Analysis

v0.2.6

GPL (>= 3)

Authors

Benjamin Leutner [cre, aut], Ned Horning [aut], Jakob Schwalb-Willmann [aut], Robert J. Hijmans [ctb]

Initial release