RStoolbox (version 0.2.4)

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.

References

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

Examples

# NOT RUN {
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)
# }