Multidimensional Wavelets for Scalable Image Decomposition: Orbital Wavelets
This work addresses a domain-specific problem in image processing by proposing a novel method for scalable wavelet-based decomposition, though it appears incremental as it builds on existing wavelet theory.
The paper tackled the problem of increasing wavelet dimensions for image decomposition by introducing orbital wavelets, which combine anti-symmetric wavelets to enable simultaneous analysis at two distinct scales in still images, with an example provided to demonstrate the approach.
Wavelets are closely related to the Schrödinger's wave functions and the interpretation of Born. Similarly to the appearance of atomic orbital, it is proposed to combine anti-symmetric wavelets into orbital wavelets. The proposed approach allows the increase of the dimension of wavelets through this process. New orbital 2D-wavelets are introduced for the decomposition of still images, showing that it is possible to perform an analysis simultaneous in two distinct scales. An example of such an image analysis is shown.