Fundamentals of digital image processing
Fundamentals of digital image processing
Robust Parameter Estimation in Computer Vision
SIAM Review
Single-Sensor Imaging: Methods and Applications for Digital Cameras
Single-Sensor Imaging: Methods and Applications for Digital Cameras
Image change detection algorithms: a systematic survey
IEEE Transactions on Image Processing
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Video conferencing without controlled lighting suffers from the spurious automatic exposure (AE) errors commonly seen in webcams. These errors cause problems for the subsequent processing and compression. For example, since video encoders do not model intensity changes, these AE errors in turn cause severe blocking artifacts. We develop a pixel-domain AE conditioning algorithm for stationary cameras that: 1) effectively reduces spurious AE changes, resulting in natural and artifact-free video; 2) allows maximum compatibility with third party components (may be transparently inserted between any camera driver and encoder/video processing engine); and 3) is fast and requires little memory. This algorithm allows inexpensive cameras to provide higher quality video conferencing. We describe the algorithm, analyze its performance exactly for a speci c video source model and validate its performance experimentally using captured video.