Adaptive Image Processing Algorithms for Printing [Hardcover]

This book presents essential algorithms for the image processing pipeline of photo-printers and accompanying software tools, offering an exposition of multiple image enhancement algorithms, smart aspect-ratio changing techniques for borderless printing and approaches for non-standard printing modes. All the techniques described are content-adaptive and operate in an automatic mode thanks to machine learning reasoning or ingenious heuristics. The first part includes algorithms, for example, red-eye correction and compression artefacts reduction, that can be applied in any photo processing application, while the second part focuses specifically on printing devices, e.g. eco-friendly and anaglyph printing. The majority of the techniques presented have a low computational complexity because they were initially designed for integration in system-on-chip. The book reflects the authors practical experience in algorithm development for industrial R&D.

Exposure Correction.- High Dynamic Range Imaging.- Image Processing using EXIF metadata.- Adaptive Sharpening.- Global and local noise reduction.- JPEG-artifacts detection and reduction.- Undesired artifact removal.- Red-eye correction.- Closed-Eye detection.- Image interpolation.- Panoramic images.- Smart cropping.- Still image retargeting.- Auto image rotation.- Anaglyph printing.- 3D printing.

Ilia V. Safonov graduated from Moscow Engineering Physics Institute (at present time National Research Nuclear University MEPhI) in 1993 as engineer-physicist. He obtained PhD degree in computer science in 1997. Since 2000, he is associated professor in the department of Computer Science and Control Systems at MEPhI. At last decade, he had senior researcher position in RnD of Samsung, Nokia and Intel. At present time, Dr. Ilia Safonov is principal research-scientist at Schlumberger Moscow Research. His interests include image and signal processing, machine learning, lc7