%0 Conference Paper %1 Richter2009c %A Richter, Thomas %B Picture Coding Symposium, 2009. PCS 2009 %C Chicago, IL, USA %D 2009 %K 2000;JPEG-XR;codestreams;digital codec;standard-constraint codecs;Code codecs;data coding coding;JPEG coding;Pipelines;Pixel;Standardization;Transform coding;perceptual compression compression;image image images;perceivable loss;perceptual quality standards;Codecs;Decoding;Humans;ISO standards;Image %P 1-4 %R 10.1109/PCS.2009.5167386 %T Perceptual Image Coding by Standard-Constraint Codecs %U http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5167386 %X A perceptual image compression codec exploits the characteristics of the human senses to minimize the perceivable quality loss of digital images under compression. Such a codec has an even higher value if the resulting codestreams are compatible to an existing standard, and are thus decodable by all-day, existing applications. This work will first describe three basic mechanisms perceptual coding is based on today, followed by strategies how to implement them in standardized environments, namely JPEG, JPEG 2000 and JPEG-XR. Following that, strategies to evaluate the success of perceptive coding are discussed, namely subjective measurements and objective quality metrics. Finally, the circle is closed back to compression codecs by showing on the example of JPEG 2000 and SSIM that quality metrics can also be used to drive the rate-allocation of a codec, and hence explore the quality judgment of a metric directly.

@inproceedings{Richter2009c, abstract = {A perceptual image compression codec exploits the characteristics of the human senses to minimize the perceivable quality loss of digital images under compression. Such a codec has an even higher value if the resulting codestreams are compatible to an existing standard, and are thus decodable by all-day, existing applications. This work will first describe three basic mechanisms perceptual coding is based on today, followed by strategies how to implement them in standardized environments, namely JPEG, JPEG 2000 and JPEG-XR. Following that, strategies to evaluate the success of perceptive coding are discussed, namely subjective measurements and objective quality metrics. Finally, the circle is closed back to compression codecs by showing on the example of JPEG 2000 and SSIM that quality metrics can also be used to drive the rate-allocation of a codec, and hence explore the quality judgment of a metric directly.}, added-at = {2016-03-03T17:45:04.000+0100}, address = {Chicago, IL, USA}, author = {Richter, Thomas}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2cb94055452e475006cdc737c387e30ed/rainerreichel}, booktitle = {Picture Coding Symposium, 2009. PCS 2009}, doi = {10.1109/PCS.2009.5167386}, interhash = {37fffcc99749f072c9e80b3dbe833a6c}, intrahash = {cb94055452e475006cdc737c387e30ed}, keywords = {2000;JPEG-XR;codestreams;digital codec;standard-constraint codecs;Code codecs;data coding coding;JPEG coding;Pipelines;Pixel;Standardization;Transform coding;perceptual compression compression;image image images;perceivable loss;perceptual quality standards;Codecs;Decoding;Humans;ISO standards;Image}, month = may, pages = {1-4}, timestamp = {2016-03-04T09:57:29.000+0100}, title = {{P}erceptual {I}mage {C}oding by {S}tandard-{C}onstraint {C}odecs}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5167386}, year = 2009 }