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Contrast Optimizationnode 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.
Contrast Optimizationnode 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 Title: Contrast Optimization
- Node ID: OP_NODE_CLAHE
Contrast Optimizationnode has the following input socket:
- Image: The input image to which the CLAHE algorithm will be applied. Connect an image to this socket.
Contrast Optimizationnode has the following output socket:
- Image: The image with enhanced contrast using the CLAHE algorithm.
Contrast Optimizationnode 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.
- 1.Drag and drop the
Contrast Optimizationnode from the node library onto the canvas in AugeLab Studio.
- 2.Connect the input image to the Image input socket of the
- 3.Adjust the Grid Size and Clip Limit sliders to control the parameters of the CLAHE algorithm.
- 4.Run the pipeline.
Contrast Optimizationnode will apply the CLAHE algorithm to the input image.
- 6.The image with enhanced contrast will be available at the Image output socket.
- 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.
Contrast Optimizationnode utilizes the
cv2.createCLAHEfunction from OpenCV to create the CLAHE object with the specified parameters.
- Connect the output of the
Contrast Optimizationnode 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.