Paper
19 January 2009 Interaction of image noise, spatial resolution, and low contrast fine detail preservation in digital image processing
Author Affiliations +
Proceedings Volume 7250, Digital Photography V; 72500I (2009) https://doi.org/10.1117/12.805927
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States
Abstract
We present a method to improve the validity of noise and resolution measurements on digital cameras. If non-linear adaptive noise reduction is part of the signal processing in the camera, the measurement results for image noise and spatial resolution can be good, while the image quality is low due to the loss of fine details and a watercolor like appearance of the image. To improve the correlation between objective measurement and subjective image quality we propose to supplement the standard test methods with an additional measurement of the texture preserving capabilities of the camera. The proposed method uses a test target showing white Gaussian noise. The camera under test reproduces this target and the image is analyzed. We propose to use the kurtosis of the derivative of the image as a metric for the texture preservation of the camera. Kurtosis is a statistical measure for the closeness of a distribution compared to the Gaussian distribution. It can be shown, that the distribution of digital values in the derivative of the image showing the chart becomes the more leptokurtic (increased kurtosis) the stronger the noise reduction has an impact on the image.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Uwe Artmann and Dietmar Wueller "Interaction of image noise, spatial resolution, and low contrast fine detail preservation in digital image processing", Proc. SPIE 7250, Digital Photography V, 72500I (19 January 2009); https://doi.org/10.1117/12.805927
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Cameras

Signal to noise ratio

Image processing

Image resolution

Spatial resolution

Image analysis

Denoising

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