为了在 R 中对 jpeg 图像进行分类,我想获取每个像素的 RGB 值。
我的问题:有没有办法从 R 中的 jpeg 图像中提取 RGB 通道?
您有几个要以 JPEG 格式阅读的包。在这里我使用包jpeg
:
library(jpeg)
img <- readJPEG("Rlogo.jpg")
dim(img)
[1] 76 100 3
如您所见,有 3 层:它们对应于您的 R、G 和 B 值。在每一层中,每个单元都是一个像素。
img[35:39,50:54,]
, , 1
[,1] [,2] [,3] [,4] [,5]
[1,] 0.5098039 0.5921569 0.4549020 0.3372549 0.1921569
[2,] 0.5098039 0.6000000 0.4549020 0.3372549 0.1921569
[3,] 0.5137255 0.6000000 0.4549020 0.3450980 0.1921569
[4,] 0.5215686 0.6039216 0.4627451 0.3450980 0.1921569
[5,] 0.5215686 0.6039216 0.4627451 0.3450980 0.1882353
, , 2
[,1] [,2] [,3] [,4] [,5]
[1,] 0.5882353 0.6666667 0.5098039 0.3803922 0.2156863
[2,] 0.5882353 0.6627451 0.5098039 0.3803922 0.2156863
[3,] 0.5843137 0.6627451 0.5098039 0.3764706 0.2156863
[4,] 0.5843137 0.6627451 0.5058824 0.3764706 0.2117647
[5,] 0.5843137 0.6627451 0.5058824 0.3764706 0.2156863
, , 3
[,1] [,2] [,3] [,4] [,5]
[1,] 0.7254902 0.7921569 0.6156863 0.4588235 0.2705882
[2,] 0.7254902 0.7921569 0.6156863 0.4588235 0.2784314
[3,] 0.7254902 0.7921569 0.6156863 0.4588235 0.2784314
[4,] 0.7176471 0.7921569 0.6156863 0.4666667 0.2862745
[5,] 0.7176471 0.7921569 0.6156863 0.4666667 0.2862745
我推荐biOps
用于图像处理的软件包。
library(biOps)
x <- readJpeg(system.file("samples", "violet.jpg", package="biOps"))
plot(x)
r <- imgRedBand(x)
plot(r)
image(x[,,1])
g <- imgGreenBand(x)
plot(g)
image(x[,,2])
b <- imgBlueBand(x)
plot(b)
image(x[,,3])
redPal <- colorRampPalette(c("black", "red"))
greenPal <- colorRampPalette(c("black", "green"))
bluePal <- colorRampPalette(c("black", "blue"))
x11(width=9, height=2.5)
par(mfcol=c(1,3))
image(x=seq(ncol(r)), y=seq(nrow(r)), z=t(r), asp=1, xaxt="n", yaxt="n", bty="n", xlab="", ylab="", main="red channel", col=redPal(256))
image(x=seq(ncol(g)), y=seq(nrow(g)), z=t(g), asp=1, xaxt="n", yaxt="n", bty="n", xlab="", ylab="", main="green channel", col=greenPal(256))
image(x=seq(ncol(b)), y=seq(nrow(b)), z=t(b), asp=1, xaxt="n", yaxt="n", bty="n", xlab="", ylab="", main="blue channel", col=bluePal(256))
我喜欢通过 RbiOps
包的方法。将数据加载到画布后,您可以将 jpg 文件从 转换imagedata
为raster
并进行进一步处理。这是我的代码:
# Required packages
library(biOps)
library(raster)
# Load and plot data
data(logo)
jpg <- logo
plot.imagedata(jpg)
# Convert imagedata to raster
rst.blue <- raster(jpg[,,1])
rst.green <- raster(jpg[,,2])
rst.red <- raster(jpg[,,3])
# Plot single raster images and RGB composite
plot(stack(rst.blue, rst.green, rst.red),
main = c("Blue band", "Green band", "Red band"))
plotRGB(stack(rst.blue, rst.green, rst.red))