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dc.contributor.authorGoswami, Hemen
dc.contributor.authorKozatis, Samuel Peter
dc.date.accessioned2017-10-04T19:44:23Z
dc.date.available2017-10-04T19:44:23Z
dc.date.issued2000-06-29
dc.identifier.citationGoswami, H., & Kozaitis, S. P. (2000). Bit-allocation considering mean absolute error for image compression. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, , 4041 63-66.en_US
dc.identifier.urihttp://hdl.handle.net/11141/1740
dc.description.abstractIn lossy image compression schemes, often some distortion measure is minimized to arrive at a desired target bit rate. The distortion measure that has been most studied is the mean-squared-error (MSE). However, perceptual quality often does not agree with the notion of minimization of mean square error1 . Since MSE can not guarantee the optimality of perceptual quality, others error measures have been investigated. Others have found strong mathematical and practical perspective to choose a different error measure other than MSE, especially for image compression2. In Ref. 2 it is argued that the mean absolute error (MAE) measure is a better error measure than MSE for image compression from a perceptual standpoint. In addition, the MSE measure fails when only a small proportion of extreme observations is present3. In this paper we develop a bit allocation algorithm to minimize the MAE rather than MSEen_US
dc.language.isoen_USen_US
dc.rightsThis published article is made available in accordance with publishers policy. It may be subject to U.S. copyright law. © (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).en_US
dc.rights.urihttp://spie.org/publications/journals/guidelines-for-authors#Terms_of_Useen_US
dc.titleBit-allocation considering mean absolute error for image compressionen_US
dc.typeConference Proceedingen_US
dc.identifier.doi10.1117/12.390488


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