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Matlab tools for "Saliency Estimation using a non-parametric vision model"
Contact: Naila Murray at <nmurray@cvc.uab.es>
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Contents
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This code package includes the following files:
- SIM_demo.m: loads a sample image and returns and displays a saliency map.
- SIM.m: converts the image to the opponent colour space, generates a saliency map for each channel and combines these maps to produce the final saliency map.
- rgb2opponent.m: converts the image to the opponent colour space.
- generate_csf.m: returns the value of the csf at a specific center-surround contrast energy and spatial scale.
- DWT.m: performs the forward DWT on one channel of an image.
- IDWT.m: performs the inverse DWT on one channel of an image.
- symmetric_filtering.m: performs 1D Gabor filtering with symmetric edge handling.
- 3.jpg and 35.jpg: sample images (from dataset of Bruce et al., Saliency Based on Information Maximization. Advances in Neural Information Processing Systems 18, 2006).
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Getting Started
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To run the demo, execute SIM_demo.m
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Suggested values for parameters
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window sizes: window sizes for computing center-surround contrast energy; suggested value of [{11:15} {25:29}]