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Journal of Flow Visualization and Image Processing

Published 4 issues per year

ISSN Print: 1065-3090

ISSN Online: 1940-4336

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 0.6 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.6 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00013 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.14 SJR: 0.201 SNIP: 0.313 CiteScore™:: 1.2 H-Index: 13

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ANALYSIS OF SYMMETRIC MULTIWAVELETS AND ITS APPLICATION FOR IMAGE COMPRESSION

Volume 9, Issue 1, 2002, 10 pages
DOI: 10.1615/JFlowVisImageProc.v9.i1.10
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ABSTRACT

Multiwavelets are the new addition to the body of wavelet theory. It is also based on the idea of multiresolution analysis (MRA). An MRA is usually generated by one scaling function. However, such wavelets cannot possess the properties of compact support, linear phase, and orthogonality simultaneously. Realized as matrix-valued filterbanks leading to wavelet bases, multiwavelets can offer these three properties simultaneously which are strongly desired in many applications, such as a fast multiresolution pyramid decomposition algorithm of image with the 2 ґ 2 matrix. To succeed using the EZW algorithms, we wish there still are some of the relationships between ancestors and their offspring. But the relationship is not very clear after the conventional iteration of multiwavelet decomposition which is similar to the scalar wavelet decomposition, and the encoding effect and efficiency are not very good. Therefore, this paper presents full new decomposition and quantization methods adapt to the symmetric property of multiwavelets. Extensive experimental results demonstrate that our techniques exhibit performance equal or superior to the conventional decomposition methods.

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