Image Color Match
This function block adjusts the color distribution of an input image to match a reference image. It is useful when you want consistent color appearance across multiple images or camera sources.
π₯ Inputs
Image RGB
The source image whose colors will be adjusted.
Reference Image
Optional. The image used as the color reference. If not provided, the block will use the source image as reference.
π€ Outputs
Image Any
The color-matched output image.
πΉοΈ Controls
This function block has no interactive controls.
π¨ Features
Matches overall color distribution between two images for visually consistent results.
Operates per color channel for finer matching.
Returns a standard image ready for further processing or display.
π Usage Instructions
Connect the source image to
Image RGB.Optionally connect a reference image to
Reference Image. If omitted, the source will be used as reference.Run the block to get the color-matched result from
Image Any.
π Evaluation
On execution, the block compares color statistics between source and reference and produces an output image whose color distribution is aligned with the reference.
π‘ Tips and Tricks
Use
Image ResizeorImage Resizerto ensure both images have the same dimensions before feeding them in (size mismatch will produce an error).Use
Color SpaceorSplit ImageandMerge Channelswhen you want to match specific channels or convert between color representations before/after matching.Use
Adjust ColorsorNormalize Imageto tweak contrast or white balance either before matching (to stabilize input) or after matching (for final visual tuning).Preview results with
Show Imageand save outcomes withImage WriteorImage Loggerfor documentation or downstream processing.
π οΈ Troubleshooting
If you see an error about image sizes, make sure both images have identical width and height and use
Image Resizeto correct mismatches.If colors look unnatural after matching, try preprocessing with
Normalize Imageor adjusting per-channel values withAdjust Colorsbefore running the block.For batch processing many images, consider resizing and normalizing inputs first to obtain consistent results across the set.
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