淡江大學機構典藏:Item 987654321/81303
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/81303


    Title: A fast discrete wavelet transform algorithm for visual processing applications
    Authors: Hsia, Chih-Hsien;Guo, Jing-Ming;Chiang, Jen-Shiun
    Contributors: 淡江大學電機工程學系
    Keywords: Discrete Wavelet Transform;Symmetric Mask-based Discrete Wavelet Transform;Transpose memory;Critical path
    Date: 2012-01
    Issue Date: 2013-03-08 16:34:01 (UTC+8)
    Publisher: New York: Elsevier Science
    Abstract: For visual processing applications, the two-dimensional (2-D) Discrete Wavelet Transform (DWT) can be used to decompose an image into four-subband images. However, when a single band is required for a specific application, the four-band decomposition demands a huge complexity and transpose time. This work presents a fast algorithm, namely 2-D Symmetric Mask-based Discrete Wavelet Transform (SMDWT), to address some critical issues of the 2-D DWT. Unlike the traditional DWT involving dependent decompositions, the SMDWT itself is subband processing independent, which can significantly reduce complexity. Moreover, DWT cannot directly obtain target subbands as mentioned, which leads to an extra wasting in transpose memory, critical path, and operation time. These problems can be fully improved with the proposed SMDWT. Nowadays, many applications employ DWT as the core transformation approach, the problems indicated above have motivated researchers to develop lower complexity schemes for DWT. The proposed SMDWT has been proved as a highly efficient and independent processing to yield target subbands, which can be applied to real-time visual applications, such as moving object detection and tracking, texture segmentation, image/video compression, and any possible DWT-based applications.
    Relation: Signal Processing 92(1), pp.89-106
    DOI: 10.1016/j.sigpro.2011.06.009
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

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