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Defect pixel interpolation for lossy compression of camera raw data

: Schöberl, M.; Seiler, J.; Kaup, A.; Keinert, J.; Foessel, S.


Said, A. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.; Society for Imaging Science and Technology -IS&T-:
Visual information processing and communication III : 24 - 26 January 2012, Burlingame, California, United States ; proceedings; part of IS&T/SPIE electronic imaging, science and technology
Bellingham, WA: SPIE, 2012 (Proceedings of SPIE 8305)
ISBN: 978-0-8194-8952-4
Paper 83050N
Conference "Visual Information Processing and Communication" <3, 2012, Burlingame/Calif.>
Electronic Imaging: Science and Technology Symposium (IS&T) <2012, Burlingame/Calif.>
Fraunhofer IIS ()

The image processing pipeline of a traditional digital camera is often limited by processing power. A better image quality could be generated only if more complexity was allowed. In a raw data workflow most algorithms are executed off-camera. This allows the use of more sophisticated algorithms for increasing image quality while reducing camera complexity. However, this requires a major change in the processing pipeline: a lossy compression of raw camera images might be used early in the pipeline. Subsequent off-camera algorithms then need to work on modified data. We analyzed this problem for the interpolation of defect pixels. We found that a lossy raw compression spreads the error from uncompensated defects over many pixels. This leads to a problem as this larger error cannot be compensated after compression. The use of high quality, high complexity algorithms in the camera is also not an option. We propose a solution to this problem: Inside the camera only a simple and low complexity defect pixel interpolation is used. This significantly reduces the compression error for neighbors of defects. We then perform a lossy raw compression and compensate for defects afterwards. The high complexity defect pixel interpolation can be used off-camera. This leads to a high image quality while keeping the camera complexity low.