Mahmoud R. El-Sakka and Mohamed S. Kamel, "A Segmentation
Criterion for Digital Image Compression", IEEE International
Conference on Acoustics, Speech and Signal Processing,
ICASSP'1995, pp. 2551-2554, May 1995, Detroit, Michigan, USA.
This paper is concerned with segmenting light intensity
images for the sake of compressing them using lossy
compression techniques. Among the most commonly used
techniques for image segmentation is Quad-tree partitioning.
In this technique, block variance based criteria are usually
used to measure the smoothness of the segmented blocks and to
consequently classify them. Block variance, however, does
not consider the pixel value distribution within the block.
Instead of using the block variance as a segmentation and
classification measure, we propose using the mean squared
deviation from the neighboring pixels mean. The proposed
measure is capable of differentiating between blocks not only
according to block pixel values but also according to their
distribution within the block. This leads to a much better
image segmentation and consequently to higher image
compression ratios with lower image degradation. The results
show the superiority of the proposed measure over the !
block variance measure.