Defect Pixel Interpolation for Lossy Compression of Camera Raw Data

摘要

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.