Uwe Artmann
Technical at Image Engineering GmbH & Co KG
SPIE Involvement:
Author | Instructor
Publications (7)

Proceedings Article | 27 February 2015 Paper
Proc. SPIE. 9404, Digital Photography XI
KEYWORDS: Stars, Imaging systems, Spatial frequencies, Cameras, Signal attenuation, Image processing, Denoising, Image resolution, Image quality, Signal processing

Proceedings Article | 7 March 2014 Paper
Proc. SPIE. 9023, Digital Photography X
KEYWORDS: Visualization, Imaging systems, Spatial frequencies, Cameras, Denoising, Imaging devices, Image quality, Image enhancement, Zoom lenses, Galactic astronomy

Proceedings Article | 7 March 2013 Paper
Proc. SPIE. 8667, Multimedia Content and Mobile Devices
KEYWORDS: Digital signal processing, Digital image processing, Spatial frequencies, Cameras, Image processing, Video, Imaging devices, Image quality, Signal processing, Image enhancement

Proceedings Article | 25 January 2012 Paper
Proc. SPIE. 8293, Image Quality and System Performance IX
KEYWORDS: Detection and tracking algorithms, Spatial frequencies, Cameras, Signal attenuation, Denoising, Image resolution, Digital cameras, Image analysis, Image quality, Picosecond phenomena

Proceedings Article | 18 January 2010 Paper
Proc. SPIE. 7529, Image Quality and System Performance VII
KEYWORDS: Stars, Modulation, Spatial frequencies, Cameras, Image processing, Denoising, Digital cameras, Image quality, Signal processing, Modulation transfer functions

Showing 5 of 7 publications
Course Instructor
SC1058: Image Quality and Evaluation of Cameras In Mobile Devices
Digital and mobile imaging camera system performance is determined by a combination of sensor characteristics, lens characteristics, and image-processing algorithms. As pixel size decreases, sensitivity decreases and noise increases, requiring a more sophisticated noise-reduction algorithm to obtain good image quality. Furthermore, small pixels require high-resolution optics with low chromatic aberration and very small blur circles. Ultimately, there is a tradeoff between noise, resolution, sharpness, and the quality of an image. This short course provides an overview of "light in to byte out" issues associated with digital and mobile imaging cameras. The course covers, optics, sensors, image processing, and sources of noise in these cameras, algorithms to reduce it, and different methods of characterization. Although noise is typically measured as a standard deviation in a patch with uniform color, it does not always accurately represent human perception. Based on the "visual noise" algorithm described in ISO 15739, an improved approach for measuring noise as an image quality aspect will be demonstrated. The course shows a way to optimize image quality by balancing the tradeoff between noise and resolution. All methods discussed will use images as examples.
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