Paper
7 June 1996 Hyperacuity processing
Author Affiliations +
Abstract
A digital image smoothing procedure is described that meets two requirements inferred from a recent model of biological vision. First, the smoothed image is a linear combination of basis functions formed by convolving a Gaussian function with each pixel. Second, the linear coefficients are evaluated by requiring that the integral of the smoothed image over each pixel equal the product of the gray value and area of that pixel. These requirement are in accordance with a model of visual hyperacuity that explains the ability of biological vision systems to resolve some image details that are much smaller than system photoreceptors. The procedure is demonstrated and compared with standard Gaussian convolution smoothing for both a simple one- dimensional example and a practical corner-of-an-eye test image.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven C. Gustafson, Gordon R. Little, and Theresa A. Tuthill "Hyperacuity processing", Proc. SPIE 2751, Hybrid Image and Signal Processing V, (7 June 1996); https://doi.org/10.1117/12.242005
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KEYWORDS
Convolution

Image processing

Visual process modeling

Digital imaging

Visualization

Digital image processing

Spatial resolution

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