A fast Discrete Wavelet Transform algorithm for visual processing applications

Authors:
Chih-Hsien Hsia;Jing-Ming Guo;Jen-Shiun Chiang
Affiliations:
Multimedia Signal Processing Lab., Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei city, Taiwan;Multimedia Signal Processing Lab., Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei city, Taiwan;Advanced Mixed-Operation System Lab., Department of Electrical Engineering, Tamkang University, New Taipei city, Taiwan
Venue:
Signal Processing
Year:
2012

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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.