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AugeLab Studio Manual
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Contrast Optimization

Contrast Optimization (CLAHE) Node Documentation

The Contrast Optimization node in AugeLab Studio applies the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm to enhance the contrast of an input image. This technique is particularly useful for improving the visibility of details in images with uneven lighting or low contrast.

Node Overview

The Contrast Optimization node applies the CLAHE algorithm to the input image. It partitions the image into small tiles and performs histogram equalization on each tile individually. This localized contrast enhancement helps to preserve the details while avoiding overamplification of noise.

Node Properties

  • Node Title: Contrast Optimization
  • Node ID: OP_NODE_CLAHE

Inputs

The Contrast Optimization node has the following input socket:
  • Image: The input image to which the CLAHE algorithm will be applied. Connect an image to this socket.

Outputs

The Contrast Optimization node has the following output socket:
  • Image: The image with enhanced contrast using the CLAHE algorithm.

Node Configuration

The Contrast Optimization node provides the following configuration options:
  • Grid Size: Adjust the size of the grid used for partitioning the image into tiles. The value determines the number of tiles in both the x and y directions.
  • Clip Limit: Set the clip limit, which determines the threshold for contrast limiting. Pixels with a value above this limit will be clipped and redistributed to the lower bins during histogram equalization.

Usage

  1. 1.
    Drag and drop the Contrast Optimization node from the node library onto the canvas in AugeLab Studio.
  2. 2.
    Connect the input image to the Image input socket of the Contrast Optimization node.
  3. 3.
    Adjust the Grid Size and Clip Limit sliders to control the parameters of the CLAHE algorithm.
  4. 4.
    Run the pipeline.
  5. 5.
    The Contrast Optimization node will apply the CLAHE algorithm to the input image.
  6. 6.
    The image with enhanced contrast will be available at the Image output socket.

Notes

  • The CLAHE algorithm is particularly useful for images with uneven lighting or low contrast.
  • Adjust the Grid Size parameter to control the size of the tiles used for histogram equalization. Larger grid sizes capture larger-scale variations in the image, while smaller grid sizes enhance smaller details.
  • The Clip Limit parameter determines the threshold for contrast limiting. Higher values allow more contrast enhancement but may result in amplification of noise. Experiment with different values to achieve the desired balance between contrast enhancement and noise suppression.
  • The Contrast Optimization node utilizes the cv2.createCLAHE function from OpenCV to create the CLAHE object with the specified parameters.
  • Connect the output of the Contrast Optimization node to other nodes in the pipeline for further processing or analysis.
That concludes the documentation for the Contrast Optimization (CLAHE) node in AugeLab Studio. This node provides a powerful tool for enhancing the contrast of images with uneven lighting or low contrast, enabling you to reveal more details and improve the visual quality of your images.