Abstract:The basic theory of Jacquin's fractal block coding is to approximate a natural image by its partial subdivided parts, given that the parts resemble the whole at either the same scale or different scales. The fact that self-similarity most commonly exists within an entire natural image leads to the development of the proposed method that uses arc as the fractal descriptor, in which an arc commonly exists within the entire natural image, named as Arc-Descriptor Fractal Coding (ADFC) method. In the ADFC, each range block is approximated by using the selected arc-descriptor from an optimal pool. This paper experimentally demonstrates the ADFC method on Java and the ADFC system is verified with 5 medical images. The experimental results indicate the ADFC method can encode and decode the experimental images effectively. The PSNR of the images after encoding can reach 30 dB at limited cost while the CR is less than 17%. The ADFC outperforms Jacquin's method under the comparison of the number of search in matching process. We conclude that the ADFC successfully encodes and decodes image in an efficient search during encoding phase without noticeable loss of image quality.
Burstiness is an important network feature. Many studies apply crude methods using "burst" or flow size to diagnose bursty flows, but these approaches cannot reveal traffic details. Using the self-similarity of network flow, the study transforms the time-domain traffic into space-domain data, and adopts the variations of fractal dimensions to determine the variations of burstiness. The resulting variations of burstiness indicate the irregular situation of network. Experimental results show that the variation of the fractal dimension is proportional to the variation of burstiness. Thus, a variation that exceeds a pre-defined threshold indicates irregular traffic. Triggering a simple alarm upon detecting irregular traffic can ameliorate the following traffic. Therefore, the proposed method is an effective gauge for flow monitoring because it watches the fractal dimensions derived from network traffic. The proposed method can help network administrators monitor traffic in detail and better manage their networks.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.