Wolfram Language

Multiscale Feature Detection

Most filters are applied to an image at a fixed scale, while image features occur at all scales. ImagePyramid creates different resolutions of an image. Results of filtering all levels of image pyramid can be combined to create a multiscale feature detection. This example shows gradient filtering as well as saliency filtering of images in multiscale.

Apply a gradient filter at several scales simultaneously.

Apply gradient filtering to all levels of the pyramid and reconstruct assuming a Laplacian pyramid to add up features extracted from all levels.

Compare the result with the gradient filter at a single fixed scale.

Compute interesting or important regions of an image using a multiscale saliency filtering.

Apply a saliency filter to all levels of an image pyramid to get a multiscale result.

Compare with image saliency filtering at a single scale.

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