Image Color

Functions to adjust contrast, brightness, colors of the image. Details below.

image_modulate(image, brightness = 100, saturation = 100, hue = 100)

image_quantize(
  image,
  max = 256,
  colorspace = "rgb",
  dither = TRUE,
  treedepth = NULL
)

image_map(image, map, dither = FALSE)

image_ordered_dither(image, threshold_map)

image_channel(image, channel = "lightness")

image_separate(image, channel = "default")

image_combine(image, colorspace = "sRGB", channel = "default")

image_transparent(image, color, fuzz = 0)

image_background(image, color, flatten = TRUE)

image_colorize(image, opacity, color)

image_contrast(image, sharpen = 1)

image_normalize(image)

image_enhance(image)

image_equalize(image)

image_median(image, radius = 1)

Arguments

image: magick image object returned by image_read() or image_graph()
brightness: modulation of brightness as percentage of the current value (100 for no change)
saturation: modulation of saturation as percentage of the current value (100 for no change)
hue: modulation of hue is an absolute rotation of -180 degrees to +180 degrees from the current position corresponding to an argument range of 0 to 200 (100 for no change)
max: preferred number of colors in the image. The actual number of colors in the image may be less than your request, but never more.
colorspace: string with a colorspace from colorspace_types for example "gray", "rgb" or "cmyk"
dither: a boolean (defaults to TRUE) specifying whether to apply Floyd/Steinberg error diffusion to the image: averages intensities of several neighboring pixels
treedepth: depth of the quantization color classification tree. Values of 0 or 1 allow selection of the optimal tree depth for the color reduction algorithm. Values between 2 and 8 may be used to manually adjust the tree depth.
map: reference image to map colors from
threshold_map: A string giving the dithering pattern to use. See the ImageMagick documentation for possible values
channel: a string with a channel from channel_types for example "alpha" or "hue" or "cyan"
color: a valid color string such as "navyblue" or "#000080". Use "none" for transparency.
fuzz: relative color distance (value between 0 and 100) to be considered similar in the filling algorithm
flatten: should image be flattened before writing? This also replaces transparency with background color.
opacity: percentage of opacity used for coloring
sharpen: enhance intensity differences in image
radius: replace each pixel with the median color in a circular neighborhood

Details

For details see Magick++ STL documentation. Short descriptions:

image_modulate adjusts brightness, saturation and hue of image relative to current.
image_quantize reduces number of unique colors in the image.
image_ordered_dither reduces number of unique colors using a dithering threshold map.
image_map replaces colors of image with the closest color from a reference image.
image_channel extracts a single channel from an image and returns as grayscale.
image_transparent sets pixels approximately matching given color to transparent.
image_background sets background color. When image is flattened, transparent pixels get background color.
image_colorize overlays a solid color frame using specified opacity.
image_contrast enhances intensity differences in image
image_normalize increases contrast by normalizing the pixel values to span the full range of colors
image_enhance tries to minimize noise
image_equalize equalizes using histogram equalization
image_median replaces each pixel with the median color in a circular neighborhood

Note that colors are also determined by image properties imagetype and colorspace which can be modified via image_convert().

Examples

# manually adjust colors
logo <- image_read("logo:")
image_modulate(logo, brightness = 200)
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  
image_modulate(logo, saturation = 150)
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  
image_modulate(logo, hue = 200)
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  

# Reduce image to 10 different colors using various spaces
image_quantize(logo, max = 10, colorspace = 'gray')
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 Gray       FALSE        0 72x72  
image_quantize(logo, max = 10, colorspace = 'rgb')
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 RGB        FALSE        0 72x72  
image_quantize(logo, max = 10, colorspace = 'cmyk')
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 CMYK       FALSE        0 72x72  

image_ordered_dither(logo, 'o8x8')
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  
# Change background color
translogo <- image_transparent(logo, 'white')
image_background(translogo, "pink", flatten = TRUE)
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       TRUE         0 72x72  

# Compare to flood-fill method:
image_fill(logo, "pink", fuzz = 20)
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  

# Other color tweaks
image_colorize(logo, 50, "red")
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  
image_contrast(logo)
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  
image_normalize(logo)
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  
image_enhance(logo)
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  
image_equalize(logo)
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  
image_median(logo)
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 sRGB       FALSE        0 72x72  

# Alternate way to convert into black-white
image_convert(logo, type = 'grayscale')
#> # A tibble: 1 × 7
#>   format width height colorspace matte filesize density
#>   <chr>  <int>  <int> <chr>      <lgl>    <int> <chr>  
#> 1 GIF      640    480 Gray       FALSE        0 72x72

Arguments

Details

See also

Examples