RIS ID
33477
Abstract
In this paper, we introduce a new predictive image compression scheme that compresses an image by a set of parameters computed for individual blocks of different types. These parameters include the average and difference of the representative intensities of an image block, together with the index of a pattern associated with the block visual activity. The block representative gray values are computed through a histogram analysis of the block residuals and a pattern matching technique is employed to find the best match for the block bit-pattern from a pre-defined pattern book. To further reduce the bit rate, a predictive technique selectively predicts the parameters based on the corresponding values in the neighboring blocks. The simulation results confirm that the proposed technique can provide a high compression ratio with acceptable image quality of the compressed images.
Publication Details
Keissarian, F. 2010, 'A new predictive image compression scheme using histogram analysis and pattern matching', Proceedings 2010 Second International Conference on Computer Engineering and Applications: ICCEA 2010, IEEE, Los Alamitos, California, pp. 375-379.