Grayscale

Converts color image into shades of gray.

🖼️ Image options and parameters of grayscale method

Grayscale filter, often called a black-and-white filter, is an image processing technique used to convert a colored image into a grayscale version. In a grayscale image, each pixel is represented by a single intensity value, typically ranging from 0 (black) to 255 (white), with various shades of gray in between. This process removes color information and retains only the brightness information of the image.

Source:LennaBarbaraStandard boatMandrillPeppersHouse

Ran in 0.00μs (Infinity ops/s)

The grayscale filter essentially eliminates the color information from the image and retains only the luminance or brightness values. This type of image is often used in situations where color is not essential for understanding or conveying the visual information. Grayscale images can emphasize the tonal contrast and structural details of a scene, making them particularly useful for tasks like analyzing textures, patterns, and lighting conditions.

Kinds of images compatible with algorithm

Image property	What it means	Possible values
bitDepth	number of bits per channel	[8,16]
components	number of components	[3]
alpha	is alpha channel allowed	true

Parameters and default values

• options

Options

Property	Required	Default value
algorithm	no	luma709
keepAlpha	no	false
mergeAlpha	no	true
out	no	-

List of grayscale algorithms:

• luma709

• luma601

• max : takes maximum value among of red,green and blue.

• min : takes the minimum value of red,green and blue.

• average : takes an average value of red,green and blue.

• minmax : takes an average between the max and min values of red, green and blue.

• lightness : takes lightness component of a pixel(alias of minmax).

• red : takes a value of pixel's red channel.

• green : takes a value of pixel's green channel.

• blue : takes a value of pixel's blue channel.

• black : takes the minimum of the inverses of red, green and blue.

• cyan : takes cyan component of a pixel.

• magenta : takes magenta component of a pixel.

• yellow : takes yellow component of a pixel.

• hue : takes hue component of a pixel.

• saturation : takes a fraction from difference of minimum and maximum components of a pixel.

Implementation

Here's how grayscale filter is implemented in ImageJS:

Color Channel Separation: If the image is in color (composed of red, green, and blue channels), the grayscale filter typically processes each color channel separately. This is done to ensure that the brightness values are determined from the original color intensities.

Pixel Transformation: For each pixel in each color channel (red, green, and blue), a transformation is applied to calculate its grayscale intensity value. A common approach is to calculate the weighted average of the color channels' intensities, but there are multiple algorithms available for usage.

Applying intensity: After calculating the grayscale intensity, the resulting value is then assigned to a new copy of an image. Depending whether user keeps alpha or merges it, the value is calculated differently.