Adaptive Image Processing Algorithms for Printing [electronic resource] /
By: Safonov, Ilia V [author.].
Contributor(s): Kurilin, Ilya V [author.] | Rychagov, Michael N [author.] | Tolstaya, Ekaterina V [author.] | SpringerLink (Online service).
Series: Signals and Communication Technology: Publisher: Singapore : Springer Singapore : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XVIII, 304 p. 261 illus., 188 illus. in color. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9789811069314.Subject(s): Computer Engineering
| Speech processing systems | Optical data processing | Signal, Image and Speech Processing | Image Processing and Computer VisionDDC classification: 621.382 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.)
In:
Springer Nature eBookSummary: 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.
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.
There are no comments for this item.