Using visible SNR (vSNR) to compare the image quality of pixel binning and digital resizing

被引:8
|
作者
Farrell, Joyce [1 ]
Okincha, Mike [2 ]
Parmar, Manu [1 ,3 ]
Wandell, Brian [1 ,3 ]
机构
[1] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
[2] Omnivis Technol, Santa Clara, CA 95054 USA
[3] Stanford Univ, Dept Psychol, Stanford, CA 94305 USA
来源
DIGITAL PHOTOGRAPHY VI | 2010年 / 7537卷
关键词
sensor design; image quality; pixel binning; imaging pipeline;
D O I
10.1117/12.839149
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
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 S-CIELAB representation of a uniform field; its units are 1/Delta E. 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.
引用
收藏
页数:9
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