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Enhance image differences with control over intensity for change detection, quality inspection, and artistic effects.
The ImageEnhanceDifference+ node is designed to analyze and enhance the differences between two images. This node is particularly useful for highlighting subtle variations or changes between two images, which can be beneficial in various image analysis tasks. By applying a mathematical operation to the pixel values of the two input images, the node generates a new image that emphasizes the differences. This can be useful for tasks such as change detection, quality inspection, or artistic effects where understanding the differences between two images is crucial. The node allows you to control the intensity of the enhancement through an exponent parameter, providing flexibility in how pronounced the differences appear in the output image.
This parameter represents the first input image that you want to compare. It serves as the reference image against which the differences will be calculated. The image should be in a compatible format and resolution for accurate comparison.
This parameter represents the second input image that you want to compare with the first image. If the resolution of this image does not match the first image, it will be automatically resized to match the dimensions of the first image using a bicubic upscale method. This ensures that the comparison is accurate and meaningful.
The exponent parameter controls the intensity of the enhancement applied to the differences between the two images. It is a floating-point value that ranges from 0.00 to 1.00, with a default value of 0.75. A lower exponent value will result in a more subtle enhancement, while a higher value will make the differences more pronounced. This parameter allows you to fine-tune the output based on your specific needs.
The output of this node is a single image that highlights the differences between the two input images. The differences are enhanced based on the specified exponent value, and the resulting image is clamped to ensure that pixel values remain within a valid range. This output image can be used for further analysis, visualization, or as an input to other image processing nodes.
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