A maximum entropy Kalman filter for image compression

In this paper, we propose a novel compression method applicable to digital images. We employ Maximum Entropy (ME) as the optimization criterion and Kalman Filter (KF) as means of implementing the compressor. We will show for compression ratios comparable to those of traditional methods, such as JPEG, the high frequency components of the signal, i.e. texture and edges, are preserved. The motivation for using ME as the optimization criterion is to avoid over-smoothing of the signal associated with traditional methods based on Mean Square Error (MSE). The ME criterion is motivated by the fact that it does not make any assumptions, regarding the unobserved data.