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Image color channel separator

World's simplest image tool
Free online image into color channels converter. Just drag and drop your image here and it will automatically split into color channels. You can extract individual channels for R, G, B, A, separate C, M, Y, K channels, and individual H, S, L channels. You can also convert each extracted channel into grayscale. Created by engineers from team Browserling.
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Click here to select an image from your device, press Ctrl+V to use an image from your clipboard, drag and drop a file from desktop, or load an image from any example below.
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RGBA Image Channels
Turn images with extracted
RGBA channels to grayscale.
CMYK Image Channels
Turn images with extracted
CMYK channels to grayscale.
HSL Image Channels
Turn images with extracted
HSL channels to grayscale.

What is a image color channel separator?

learn more about this tool
This tool separates and extracts the color channels from an image. It can isolate each of the color channels from the RGBA, CMYK, and HSL color models. The RGBA color model consists of four channels: R (Red), G (Green), B (Blue), and A (Alpha, transparency). The Red channel isolates the intensity of red tones in the image. The Green channel captures the intensity of green tones in the image. The Blue channel reveals the intensity of blue tones in the image. The Alpha channel is used to specify transparency information. The CMYK color model contains four channels: C (Cyan), M (Magenta), Y (Yellow), K (Key/Black). The Cyan channel represents the amount of cyan ink needed to reproduce colors in the image. The Magenta channel indicates the required amount of magenta ink. The Yellow channel specifies the necessary amount of yellow ink. The Black channel, also known as the Key channel, shows the required amount of black ink. The HSL color model consists of three channels: H (Hue), S (Saturation), L (Lightness). The Hue channel represents the color itself, providing a numerical representation of where the color falls on the color wheel. The Saturation channel measures the intensity or brightness of the color, with higher values indicating more vivid colors. The Lightness channel determines how light or dark the color is. By separating the color channels, you can analyze and understand the composition of the image in terms of its red, green, blue, and other color components. Additionally, if needed, you can convert the extracted channel of the image into grayscale tones. Image-abulous!

Image color channel separator examples

Click to use
Separate Red Image Channel
This example separates the red channel from the RGBA color model of the image and displays it on the screen. The output represents each pixel of the image as the color RGBA(R, 0, 0, 1), where the R channel (Red) ranges from 0 to 255, indicating the amount of red color in each pixel. (Source: Pexels.)
This example separates the red channel from the RGBA color model of the image and displays it on the screen. The output represents each pixel of the image as the color RGBA(R, 0, 0, 1), where the R channel (Red) ranges from 0 to 255, indicating the amount of red color in each pixel. (Source: Pexels.)
This example separates the red channel from the RGBA color model of the image and displays it on the screen. The output represents each pixel of the image as the color RGBA(R, 0, 0, 1), where the R channel (Red) ranges from 0 to 255, indicating the amount of red color in each pixel. (Source: Pexels.)
Required options
These options will be used automatically if you select this example.
Turn images with extracted
RGBA channels to grayscale.
Turn images with extracted
CMYK channels to grayscale.
Turn images with extracted
HSL channels to grayscale.
Isolate Red, Green, and Blue
In this example, for a detailed exploration of the RGB color model, we use an image of a gradient where colors transition from red to green and then to blue. We separate the Red, Green, and Blue color channels from the image, resulting in three images that illustrate the presence of each respective hue in the original image.
In this example, for a detailed exploration of the RGB color model, we use an image of a gradient where colors transition from red to green and then to blue. We separate the Red, Green, and Blue color channels from the image, resulting in three images that illustrate the presence of each respective hue in the original image.
In this example, for a detailed exploration of the RGB color model, we use an image of a gradient where colors transition from red to green and then to blue. We separate the Red, Green, and Blue color channels from the image, resulting in three images that illustrate the presence of each respective hue in the original image.
Required options
These options will be used automatically if you select this example.
Turn images with extracted
RGBA channels to grayscale.
Turn images with extracted
CMYK channels to grayscale.
Turn images with extracted
HSL channels to grayscale.
Separate CMYK Color Channels
In this example, we transform one image into three images that represent the presence of Cyan, Magenta, and Yellow hues in the image. The three extracted channels are displayed side by side on the screen, allowing for easy comparison. As you can see, Cyan tones are only present in the area of the seawater, Yellow color is located solely in the beach area, while Magenta color is found both in the sea and on the beach. (Source: Pexels.)
In this example, we transform one image into three images that represent the presence of Cyan, Magenta, and Yellow hues in the image. The three extracted channels are displayed side by side on the screen, allowing for easy comparison. As you can see, Cyan tones are only present in the area of the seawater, Yellow color is located solely in the beach area, while Magenta color is found both in the sea and on the beach. (Source: Pexels.)
In this example, we transform one image into three images that represent the presence of Cyan, Magenta, and Yellow hues in the image. The three extracted channels are displayed side by side on the screen, allowing for easy comparison. As you can see, Cyan tones are only present in the area of the seawater, Yellow color is located solely in the beach area, while Magenta color is found both in the sea and on the beach. (Source: Pexels.)
Required options
These options will be used automatically if you select this example.
Turn images with extracted
RGBA channels to grayscale.
Turn images with extracted
CMYK channels to grayscale.
Turn images with extracted
HSL channels to grayscale.
Illustrate a Transparency Property
In this example, we extract the Alpha channel from an image of a rubber plant on a transparent background. The Alpha channel defines the transparency levels of each pixel, ranging from 0 (completely transparent) to 1 (completely opaque). All other RGB channels are set to zero, resulting in opaque areas appearing as black and transparent regions as fully transparent. (Source: Pexels.)
In this example, we extract the Alpha channel from an image of a rubber plant on a transparent background. The Alpha channel defines the transparency levels of each pixel, ranging from 0 (completely transparent) to 1 (completely opaque). All other RGB channels are set to zero, resulting in opaque areas appearing as black and transparent regions as fully transparent. (Source: Pexels.)
In this example, we extract the Alpha channel from an image of a rubber plant on a transparent background. The Alpha channel defines the transparency levels of each pixel, ranging from 0 (completely transparent) to 1 (completely opaque). All other RGB channels are set to zero, resulting in opaque areas appearing as black and transparent regions as fully transparent. (Source: Pexels.)
Required options
These options will be used automatically if you select this example.
Turn images with extracted
RGBA channels to grayscale.
Turn images with extracted
CMYK channels to grayscale.
Turn images with extracted
HSL channels to grayscale.
Separate Hue, Saturation, and Light
This example separates an image of an adorable penguin family into the Hue, Saturation, and Lightness channels. The Hue channel reveals that the penguins' bellies and necks consist of yellow-green hues, while their backs exhibit blue tones. The Saturation channel indicates that the highest saturation is found in the penguins' cheeks. The Lightness channel shows the extent to which the lighter areas of the bellies differ from the darker areas of their backs. (Source: Pexels.)
This example separates an image of an adorable penguin family into the Hue, Saturation, and Lightness channels. The Hue channel reveals that the penguins' bellies and necks consist of yellow-green hues, while their backs exhibit blue tones. The Saturation channel indicates that the highest saturation is found in the penguins' cheeks. The Lightness channel shows the extent to which the lighter areas of the bellies differ from the darker areas of their backs. (Source: Pexels.)
This example separates an image of an adorable penguin family into the Hue, Saturation, and Lightness channels. The Hue channel reveals that the penguins' bellies and necks consist of yellow-green hues, while their backs exhibit blue tones. The Saturation channel indicates that the highest saturation is found in the penguins' cheeks. The Lightness channel shows the extent to which the lighter areas of the bellies differ from the darker areas of their backs. (Source: Pexels.)
Required options
These options will be used automatically if you select this example.
Turn images with extracted
RGBA channels to grayscale.
Turn images with extracted
CMYK channels to grayscale.
Turn images with extracted
HSL channels to grayscale.
Grayscale CMYK Channels
In this example, we first separate the Cyan, Magenta, and Yellow hues from the image, and then convert them to grayscale tones. Gray tones allow for a more precise comparison of the image's color channels since the hue and brightness of each channel will not affect the visual assessment. (Source: Pexels.)
In this example, we first separate the Cyan, Magenta, and Yellow hues from the image, and then convert them to grayscale tones. Gray tones allow for a more precise comparison of the image's color channels since the hue and brightness of each channel will not affect the visual assessment. (Source: Pexels.)
In this example, we first separate the Cyan, Magenta, and Yellow hues from the image, and then convert them to grayscale tones. Gray tones allow for a more precise comparison of the image's color channels since the hue and brightness of each channel will not affect the visual assessment. (Source: Pexels.)
Required options
These options will be used automatically if you select this example.
Turn images with extracted
RGBA channels to grayscale.
Turn images with extracted
CMYK channels to grayscale.
Turn images with extracted
HSL channels to grayscale.
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