An Improved Low Complexity Algorithm for 2-D Integer Lifting-Based Discrete Wavelet Transform Using Symmetric Mask-Based Scheme

Communication and multimedia have been developed rapidly in recent years. Digital media and services found in daily life include, such as digital cameras, VCD (Video Compact Disc), DVD (Digital Video Disc), HDTV (High-Definition TeleVision) and video conferences. Several well-known compression schemes, such as Differential Pulse Code Modulation (DPCM)-based method (Habibi & Hershel, 1974), DCT-based methods (Feig et al., 1995)(Kondo & Oishi, 2000), and Wavelet-based methods (Mallat, 1989) have been welldeveloped in recent years. The lifting-based scheme has recently provided a less-complexity solution for image/video applications, e.g., JPEG2000, Motion-JPEG2000, MPEG-4 still image coding, and MC-EZBC (Motion CompensationEmbedded Zero Block Coding). However, the real-time 2-D DWT (software-based) is still difficult to be achieved. Hence, an efficient transformation scheme for large of multimedia files is highly demanded. Filter banks for the applications of subband image/video coding were introduced in the 1990s. Wavelet coding has been studied extensively since then. Wavelet coding has been successfully applied to many applications. The most significant applications include subband coding for audio, image, video, signal analysis and representation using wavelets. In the past few years, DWT (Mallat, 1989) has been adopted in a wide range of applications including image coding and video compression, including speech analysis, numerical analysis, signal analysis, image coding, pattern recognition, computer vision and biometrics. The DWT can be viewed as a multi-resolution decomposition of a signal, meaning which decomposes a signal into several components in different wavelet frequency bands. Moreover, 2-D DWT is a modern tool for signal processing applications, such as JPEG2000 still image compression, denoising, region of interest (ROI), and watermarking. By factoring the classical wavelet filter into lifting steps, the computational complexity of the corresponding DWT can be reduced by up to 50% (Daubechies & Sweldens, 1998). The lifting steps can be easily implemented, which is different from the direct finite impulse