Computing Image Saliency Values Using Frequency-Tuned Saliency Algorithm
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In this documentation: We implement the frequency-tuned saliency algorithm to compute saliency values for images. The algorithm operates by analyzing frequency domain characteristics, typically applying difference-of-Gaussians filters in both spatial and frequency domains to highlight conspicuous regions. Based on these computed saliency values, we can effectively extract salient regions from images. This method employs weighted color and luminance features across different frequency bands to generate saliency maps. The implementation typically involves converting images to CIELAB color space, applying Gaussian pyramid decomposition, and computing center-surround differences across scales. This approach helps us better understand important regions in images and can be applied to various image processing tasks such as object detection, image segmentation, and adaptive compression.
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