Extract HSL Palette From Image

We’ve made it easy to extract a single color in the HSL format from any image you upload or paste, and now we’re taking things a step further.

extract-hsl-palette-from-image-logoWith this tool, you can create a complete HSL color palette directly from any image file. The tool analyzes the image, identifies the key colors, and then generates a collection of HSL values that reflect the original image. It’s straightforward—just click on the demo images below to try it out.

Each click on the image will capture the color from the pixel under your mouse and convert it into an HSL value. By default, the tool grabs 4 colors, but you can adjust the settings to capture more or fewer colors with each click.

HSL (Hue, Saturation, Lightness) and HSV (Hue, Saturation, Value) are both color models designed to represent colors in a more intuitive way than RGB. The main difference is how they treat brightness and saturation. HSL focuses on lightness, making it easier to work with colors in terms of shading and tints. This model is especially useful when you need to adjust colors for design purposes, as it allows for a more natural representation of highlights and shadows. HSV, by contrast, is more suited for tasks where varying the intensity of colors while maintaining hue is important, like in image processing.

Color Picker (upload image):

• Step 1 - Upload your image file.
• Step 2 - Point and click to extract palette.

New: Just paste a screenshot! Click here


Hover and click on image area to obtain color palette. You can also reset image or get a different one.

HEX
#674a32
RGB
rgb(103, 74, 50)
HSL
27°, 35%, 30%
CMYK
cmyk(0%, 28%, 51%, 60%)
HEX
#c6bbb5
RGB
rgb(198, 187, 181)
HSL
21°, 13%, 74%
CMYK
cmyk(0%, 6%, 9%, 22%)

How We Extract a HSL Color Palette from an Image

1. Loading Your Image

  • First, we load your image into our processing tool, ensuring it’s ready for analysis in its original format.

2. Analyzing Dominant Colors

  • We then analyze the image to identify the most dominant colors. This is done using techniques like K-means clustering, which helps simplify and pinpoint the key colors in the image.

3. Extracting HSL Values

  • Once the dominant colors are identified, we extract the exact HSL values for each of them, capturing the hues, saturation, and lightness that represent the colors found in the image.

4. Compiling Your HSL Palette

  • Finally, we compile these HSL values into a cohesive palette that you can use for your design projects, ensuring that the palette reflects the original image’s colors and their natural lightness.

This process provides you with a precise HSL palette that captures the true colors of your visual sample.

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