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Proceedings Paper

Using visible SNR (vSNR) to compare the image quality of pixel binning and digital resizing
Author(s): Joyce Farrell; Mike Okincha; Manu Parmar; Brian Wandell
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Paper Abstract

We introduce a new metric, the visible signal-to-noise ratio (vSNR), to analyze how pixel-binning and resizing methods influence noise visibility in uniform areas of an image. The vSNR is the inverse of the standard deviation of the SCIELAB representation of a uniform field; its units are 1/ΔE. The vSNR metric can be used in simulations to predict how imaging system components affect noise visibility. We use simulations to evaluate two image rendering methods: pixel binning and digital resizing. We show that vSNR increases with scene luminance, pixel size and viewing distance and decreases with read noise. Under low illumination conditions and for pixels with relatively high read noise, images generated with the binning method have less noise (high vSNR) than resized images. The binning method has noticeably lower spatial resolution. The binning method reduces demands on the ADC rate and channel throughput. When comparing binning and resizing, there is an image quality tradeoff between noise and blur. Depending on the application users may prefer one error over another.

Paper Details

Date Published: 18 January 2010
PDF: 9 pages
Proc. SPIE 7537, Digital Photography VI, 75370C (18 January 2010); doi: 10.1117/12.839149
Show Author Affiliations
Joyce Farrell, Stanford Univ. (United States)
Mike Okincha, OmniVision Technologies, Inc. (United States)
Manu Parmar, Stanford Univ. (United States)
Brian Wandell, Stanford Univ. (United States)


Published in SPIE Proceedings Vol. 7537:
Digital Photography VI
Francisco Imai; Nitin Sampat; Feng Xiao, Editor(s)

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