Wavelet array decomposition of images using a Hermite sieve |
| |
Authors: | Y V Venkatesh K Ramani R Nandini |
| |
Affiliation: | (1) Computer Vision and Artificial Intelligence Laboratory, Department of Electrical Engineering, Indian Institute of Science, 560 012 Bangalore, India |
| |
Abstract: | Generalized Hermite polynomials are used in a novel way to arrive at a multi-layered representation of images. This representation,
which is centred on the creation of a new class ofwavelet arrays, is (i) distinct from what we find in the current literature, (ii) stable, and (iii) in the manner of standard transforms,
transforms the image, explicitly, into matrices of coefficients, reminiscent of Fourier series,but at various scales, controlled by ascale parameter. Among the other properties of the wavelet arrays, (a) the shape of the resolution cell in the ‘phase-space’ is
variable even at a specified scale, depending on the nature of the signal under consideration; and (b) a systematic procedure
is given for extracting the zero-crossings from the coefficients at various scales. This representation has been successfully
applied to both synthetic and natural images, including textures. |
| |
Keywords: | Image representation wavelet transform multi-resolution generalized Hermite polynomials scale space signal decomposition windowed Fourier transform Fourier series zero-crossings |
本文献已被 SpringerLink 等数据库收录! |
|