Bit allocation considering mean absolute error for image compression

Hemen Goswami; Samuel Peter Kozaitis

doi:10.1117/12.390488

29 June 2000 Bit allocation considering mean absolute error for image compression

Proceedings Volume 4041, Visual Information Processing IX; (2000) https://doi.org/10.1117/12.390488
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

In 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 MSE

Citation Download Citation

Hemen Goswami and Samuel Peter Kozaitis "Bit allocation considering mean absolute error for image compression", Proc. SPIE 4041, Visual Information Processing IX, (29 June 2000); https://doi.org/10.1117/12.390488

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