Abstract
In this paper we analyze basic mask creation methods for intelligent image coding using saliency maps. For saliency maps based image coding we use specific extension of SPIHT algorithm called SM SPIHT related to region of interest encoding but extending this approach further, ending with individual weight of importance for each pixel in image using the form of saliency map. This approach is proved to be effective. In this article we analyze impact of different basic hierarchical mask creation methods, which have impact on error separation between salient and not salient parts of the image. The results indicate that proposed mask creation method outperforms JPEG2000 based mask tree creation method.
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