%0 Conference Paper %1 he:2005:EH %A He, Jingsong %A Wang, Xufa %A Zhang, Min %A Wang, Jiying %A Fang, Qiansheng %B Proceedings of the 2005 NASA/DoD Conference on Evolvable Hardware %C Washington, DC, USA %D 2005 %E Lohn, Jason %E Gwaltney, David %E Hornby, Gregory %E Zebulum, Ricardo %E Keymeulen, Didier %E Stoica, Adrian %I IEEE Press %K EHW algorithms, genetic programming, %P 160--164 %T New Research on Scalability of Lossless Image Compression by GP Engine %U http://doi.ieeecomputersociety.org/10.1109/EH.2005.35 %X By introducing the optimal linear predictive code technic into the dynamic issue of loss less image compression, this paper presented a less complexity fitness function for Genetic Programming engine, which can reduce the cost of computational time in each evaluation for individual greatly, and can also provide further benefit with the scalability issue. To make the speed of large image compression faster in condition of not increasing the cost of computational resource and time, evaluating mechanism in the field of machine learning was used to help Genetic Programming, and the scalability issue was mapped to the task of making the approach accuracy best from lower speed sampling to higher speed sampling in the field of signal processing. In experiments for compressing large images, the cost of computational time was reduced evidently and efficiently. %@ 0-7695-2399-4

@inproceedings{he:2005:EH, abstract = {By introducing the optimal linear predictive code technic into the dynamic issue of loss less image compression, this paper presented a less complexity fitness function for Genetic Programming engine, which can reduce the cost of computational time in each evaluation for individual greatly, and can also provide further benefit with the scalability issue. To make the speed of large image compression faster in condition of not increasing the cost of computational resource and time, evaluating mechanism in the field of machine learning was used to help Genetic Programming, and the scalability issue was mapped to the task of making the approach accuracy best from lower speed sampling to higher speed sampling in the field of signal processing. In experiments for compressing large images, the cost of computational time was reduced evidently and efficiently.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Washington, DC, USA}, author = {He, Jingsong and Wang, Xufa and Zhang, Min and Wang, Jiying and Fang, Qiansheng}, biburl = {https://www.bibsonomy.org/bibtex/2888d7e53a5a00921e34fdecb54d7604a/brazovayeye}, booktitle = {Proceedings of the 2005 NASA/DoD Conference on Evolvable Hardware}, editor = {Lohn, Jason and Gwaltney, David and Hornby, Gregory and Zebulum, Ricardo and Keymeulen, Didier and Stoica, Adrian}, interhash = {0042bf02f6e94428350dbd53fdc5bde3}, intrahash = {888d7e53a5a00921e34fdecb54d7604a}, isbn = {0-7695-2399-4}, keywords = {EHW algorithms, genetic programming,}, month = {29 June-1 July}, notes = {EH2005 IEEE Computer Society Order Number P2399}, organisation = {NASA, DoD}, pages = {160--164}, publisher = {IEEE Press}, publisher_address = {IEEE Service Center 445 Hoes Lane Asia P.O. Box 1331 Piscataway, NJ 08855-1331}, timestamp = {2008-06-19T17:41:15.000+0200}, title = {New Research on Scalability of Lossless Image Compression by {GP} Engine}, url = {http://doi.ieeecomputersociety.org/10.1109/EH.2005.35}, year = 2005 }