Phase-Stretch Adaptive Gradient-Field Extractor (PAGE)
This work addresses edge detection for computer vision applications, but it appears incremental as it builds on existing physics-inspired methods without claiming broad SOTA improvements.
The authors tackled edge detection in digital images by developing PAGE, an algorithm inspired by electromagnetic diffraction and dispersion, which identifies edges, orientations, and sharpness, performing exceptionally well in low-light and low-contrast conditions.
Phase-Stretch Adaptive Gradient-Field Extractor (PAGE) is an edge detection algorithm that is inspired by physics of electromagnetic diffraction and dispersion. A computational imaging algorithm, it identifies edges, their orientations and sharpness in a digital image where the image brightness changes abruptly. Edge detection is a basic operation performed by the eye and is crucial to visual perception. PAGE embeds an original image into a set of feature maps that can be used for object representation and classification. The algorithm performs exceptionally well as an edge and texture extractor in low light level and low contrast images. This manuscript is prepared to support the open-source code which is being simultaneously made available within the GitHub repository https://github.com/JalaliLabUCLA/Phase-Stretch-Adaptive-Gradient-field-Extractor/.