Paper
6 April 1998 Spectrum warping: a new framework for working with texture
Kunal Mukherjee
Author Affiliations +
Proceedings Volume 3304, Nonlinear Image Processing IX; (1998) https://doi.org/10.1117/12.304602
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States
Abstract
The frequency spectra are concise, but complete descriptors of image texture. The peaks in the spectrum, or equivalently, the dominant poles in an autoregressive model represent the granularity and orientation of the texture -- two of its most salient visual characteristics. In this paper, a Gaussian model is developed for the peaks of the frequency spectra, and simple warping functions are defined on these peaks, to formulate a diverse and powerful set of operators, e.g. shape from texture, planar texture rendering using perspective projection, frontalization, shift and scaling of texture. Our approach to shape from texture converts perspective distortion of texture into a range image by warping the spectrum, and our planar rendering technique warps the spectrum to simulate the perspective effect. Thus, our unified texture model gives rise to real-time algorithms for computer vision, graphics and multi-media, which are direct, and are based on local modeling rather than global optimization.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kunal Mukherjee "Spectrum warping: a new framework for working with texture", Proc. SPIE 3304, Nonlinear Image Processing IX, (6 April 1998); https://doi.org/10.1117/12.304602
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KEYWORDS
Fourier transforms

Visualization

Cameras

Distortion

Algorithm development

Autoregressive models

Transform theory

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