An Efficient Folded Architecture for Lifting-Based Discrete Wavelet Transform

In this brief an efficient folded architecture (EFA) for lifting-based discrete wavelet transform (DWT) is presented. The proposed EFA is based on a novel form of the lifting scheme that is given in this brief. Due to this form, the conventional serial operations of the lifting data flow can be optimized into parallel ones by employing parallel and pipeline techniques. The corresponding optimized architecture (OA) has short critical path latency and is repeatable. Further, utilizing this repeatability, the EFA is derived from the OA by employing the fold technique. For the proposed EFA, hardware utilization achieves 100%, and the number of required registers is reduced. Additionally, the shift-add operation is adopted to optimize the multiplication; thus, the proposed architecture is more suitable for hardware implementation. Performance comparisons and field-programmable gate array (FPGA) implementation results indicate that the proposed EFA possesses better performances in critical path latency, hardware cost, and control complexity.     

VLSI Architecture for Lifting-Based Shape-Adaptive Discrete Wavelet Transform with Odd-Symmetric Filters

In this paper, a VLSI architecture for lifting-based shape-adaptive discrete wavelet transform (SA-DWT) with odd-symmetric filters is proposed. The proposed architecture is comprised of a stage-based boundary extension strategy and the shape-adaptive boundary handling units. The former could reduce the complexity of multiplexers that are introduced to solve the shape-adaptive boundary extension. The latter consists of two multiplexers and can solve the shape-adaptive boundary extension locally without any additional register. Two case studies are presented, including the JPEG 2000 default (9, 7) filter and MPEG-4 default (9, 3) filter. According to comparison results with previous architectures, the efficiency of the proposed architectures is proven.Chao-Tsung Huang was born in Kaohsiung, Taiwan in 1979. He received the B.S. degree from the Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan in 2001. He is currently working toward the Ph.D. degree at the Graduate Institute of Electronics Engineering, National Taiwan University. His major research interests include VLSI design and implementation for 1-D, 2-D, and 3-D Discrete Wavelet Transform. cthuang@video.ee.ntu.edu.twPo-Chih Tseng was born in Tao-Yuan, Taiwan in 1977. He received the B.S. degree in Electrical and Control Engineering from National Chiao Tung University in 1999 and the M.S. degree in Electrical Engineering from National Taiwan University in 2001. He currently is pursuing the Ph.D. degree at the Graduate Institute of Electronics Engineering, Department of Electrical Engineering, National Taiwan University. His research interests include VLSI design and implementation for signal processing systems, energy-efficient reconfigurable computing for multimedia systems, and power-aware image and video coding systems. pctseng@video.ee.ntu.edu.twLiang-Gee Chen (S84–M86–SM94–F01) received the B.S., M.S., and Ph.D. degrees in electrical engineering from National Cheng Kung University, Tainan, Taiwan, R.O.C., in 1979, 1981, and 1986, respectively.In 1988, he joined the Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, R.O.C. During 1993–1994, he was a Visiting Consultant in the DSP Research Department, AT&T Bell Labs, Murray Hill, NJ. In 1997, he was a Visiting Scholar of the Department of Electrical Engineering, University of Washington, Seattle. Currently, he is Professor at National Taiwan University, Taipei, Taiwan, R.O.C. His current research interests are DSP architecture design, video processor design, and video coding systems.Dr. Chen has served as an Associate Editor of IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY since 1996, as Associate Editor of the IEEE TRANSACTIONS ON VLSI SYSTEMS since 1999, and as Associate Editor of IEEE TRANSACTIONS CIRCUITS AND SYSTEMS II since 2000. He has been the Associate Editor of the Journal of Circuits, Systems, and Signal Processing since 1999, and a Guest Editor for the Journal of Video Signal Processing Systems. He is also the Associate Editor of the PROCEEDINGS OF THE IEEE. He was the General Chairman of the 7th VLSI Design/CAD Symposium in 1995 and of the 1999 IEEE Workshop on Signal Processing Systems: Design and Implementation. He is the Past-Chair of Taipei Chapter of IEEE Circuits and Systems (CAS) Society, and is a member of the IEEE CAS Technical Committee of VLSI Systems and Applications, the Technical Committee of Visual Signal Processing and Communications, and the IEEE Signal Processing Technical Committee of Design and Implementation of SP Systems. He is the Chair-Elect of the IEEE CAS Technical Committee on Multimedia Systems and Applications. During 2001–2002, he served as a Distinguished Lecturer of the IEEE CAS Society. He received the Best Paper Award from the R.O.C. Computer Society in 1990 and 1994. Annually from 1991 to 1999, he received Long-Term (Acer) Paper Awards. In 1992, he received the Best Paper Award of the 1992 Asia-Pacific Conference on circuits and systems in the VLSI design track. In 1993, he received the Annual Paper Award of the Chinese Engineer Society. In 1996 and 2000, he received the Outstanding Research Award from the National Science Council, and in 2000, the Dragon Excellence Award from Acer. He is a member of Phi Tan Phi. lgchen@video.ee.ntu.edu.tw     

一维离散小波变换的VLSI设计

文章提出了一种离散小波变换的VLSI结构。这种结构由四部分构成：输入延迟单元、寄存器单元、滤波器单元和控制单元。该结构采用了递归金字塔算法(RPA)取代传统的PA算法。只用一组滤波器即可完成所有级别的小波运算。同时，结合Short-Length FIR技术，以减少乘法和加法的运算次数。在寄存器单元的设计上，采用了Lifetime Analysis技术，结合Forward-Backward Register Allocation(FBRA)方法，使寄存器的数目降至最低。     

应用于JPEG2000的5/3提升小波的VLSI结构设计

提出一种基于提升算法（lifting scheme）实现JPEG2000编码系统中的二维离散小波变换（Discrete Wavelet Transform）的并行阵列式的VLSI结构设计方法.该结构由一个行处理器和一个列处理器组成,行、列处理器通过时分复用同时进行滤波,用优化的移位加操作替代乘法操作,采用嵌入式数据延拓算法处理边界延拓.整个结构采用流水线设计方法,减少了运算量,提高了硬件资源利用率,该结构可应用于JPEG2000图像编码芯片中.     

An Efficient VLSI Architecture for the Computation of 1-D Discrete Wavelet Transform

This paper presents a new architecture for VLSI implementation of the one dimensional Discrete Wavelet Transform (DWT). The architecture uses single filter for generation of both the DWT coefficients and scaling function for orthogonal wavelets as opposed to the conventional two filter approach. For multilevel decomposition, the fold back architecture principle, which interleaves the decimated scaling function back into the filter for subsequent levels, is applied. Limited use of memory in the design enables efficient implementation of the DWT computation in VLSI.     

一种快速高效的二维一级小波变换的硬件实现

提出了一种针对9/7小波滤波器的二维一级小波变换的硬件平台,整体结构采用流水方式实现,数据分组输入,列变换采用多个小波变换单元,行变换模块为可重构硬件结构,行列变换之间不需要片上存储器。与已有结构相比,该结构可以通过更少的硬件资源消耗获得更高的处理速度。     

一种适合JPEG2000的离散小波变换VLSI统一结构

提出了一种基于提升算法(1ifting)的离散小波变换(DWT)统一结构。它无需额外的边界延拓过程，经配置后可适用于JPEG2000中的无损或有损小波变换。通过将边界延拓过程内嵌于离散小波变换中，可以降低功耗，减少所需内存。为了达到更高的处理速度和硬件利用率，采用了流水线和折叠结构。这种高效紧凑的离散小波变换结构适用于JPEG2000编码器和各种实时图像／视频应用系统．     

一种基于提升的二维离散小波变换VLSI架构

离散小波变换(Discrete Wavelet Transform,DWT)需要较多的运算量以及较大的存储器空间,为了使之适用于实时的图像处理应用,就需要开发特殊的架构和芯片来提高离散小波变换的运算性能。基于提升的二维DWT提出了一种新型的VLSI结构——LLSP架构,其结合逐级和基于行的架构这两者特点,带来了硬件开销和存储器空间的降低,并可以用于多提升步骤的扩展以及多级二维离散小波变换。     

一维离散小波变换VLSI结构分析设计

提升算法的推出使得离散小波变换硬件的快速实现成为可能。翻转结构在提升架构的基础上进一步提高运算速度。在此,对翻转结构的舍入误差进行了分析,在翻转结构的基础上,对提升步骤进行了合并,提出一种有效的DWT硬件实现方案。实验结果表明,通过采用流水线模式提出的这种硬件结构,在关键路径约束的条件下,可以充分利用硬件资源。     

Investigation of Lifting-Based Hardware Architectures for Discrete Wavelet Transform

This paper investigates efficient hardware architectures for implementation of 1-D and 2-D discrete wavelet transforms (DWTs). The architectures are based on the lifting scheme. We propose a general structure to minimize the number of multipliers and adders for 1-D DWTs. Compared to previous conventional architectures, the architecture presented here is more efficient in terms of the required arithmetic units. Moreover, we describe a new frame scan method for a block-based 2-D DWT structure which provides a flexible trade-off between the required internal memory size and external memory access. In contrast, other 2-D DWT structures require a fixed memory size.     

VLSI Architecture for Forward Discrete Wavelet Transform Based on B-spline Factorization

Based on B-spline factorization, a new category of architectures for Discrete Wavelet Transform (DWT) is proposed in this paper. The B-spline factorization mainly consists of the B-spline part and the distributed part. The former is proposed to be constructed by use of the direct implementation or Pascal implementation. And the latter is the part introducing multipliers and can be implemented with the Type-I or Type-II polyphase decomposition. Since the degree of the distributed part is usually designed as small as possible, the proposed architectures could use fewer multipliers than previous arts, but more adders would be required. However, many adders can be implemented with smaller area and lower speed because only few adders are on the critical path. Three case studies, including the JPEG2000 default (9, 7) filter, the (6, 10) filter, and the (10, 18) filter, are given to demonstrate the efficiency of the proposed architectures.Chao-Tsung Huang was born in Kaohsiung, Taiwan, R.O.C., in 1979. He received the B.S. degree from the Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, R.O.C., in 2001. He currently is working toward the Ph.D. degree at the Graduate Institute of Electronics Engineering, National Taiwan University. His major research interests include VLSI design and implementation for signal processing systems.Po-Chih Tseng was born in Tao-Yuan, Taiwan in 1977. He received the B.S. degree in Electrical and Control Engineering from National Chiao Tung University in 1999 and the M.S. degree in Electrical Engineering from National Taiwan University in 2001. He currently is pursuing the Ph.D. degree at the Graduate Institute of Electronics Engineering, Department of Electrical Engineering, National Taiwan University. His research interests include VLSI design and implementation for signal processing systems, energy-efficient reconfigurable computing for multimedia systems, and power-aware image and video coding systems.Liang-Gee Chen received the B.S., M.S., and Ph.D. degrees in electrical engineering from National Cheng Kung University, Tainan, Taiwan, R.O.C., in 1979, 1981, and 1986, respectively.In 1988, he joined the Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, R.O.C. During 1993–1994, he was a Visiting Consultant in the DSP Research Department, AT&T Bell Labs, Murray Hill, NJ. In 1997, he was a Visiting Scholar of the Department of Electrical Engineering, University of Washington, Seattle. Currently, he is Professor at National Taiwan University, Taipei, Taiwan, R.O.C. His current research interests are DSP architecture design, video processor design, and video coding systems.Dr. Chen has served as an Associate Editor of IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY since 1996, as Associate Editor of the IEEE TRANSACTIONS ON VLSI SYSTEMS since 1999, and as Associate Editor of IEEE TRANSACTIONS CIRCUITS AND SYSTEMS II since 2000. He has been the Associate Editor of the Journal of Circuits, Systems, and Signal Processing since 1999, and a Guest Editor for the Journal of Video Signal Processing Systems. He is also the Associate Editor of the PROCEEDINGS OF THE IEEE. He was the General Chairman of the 7th VLSI Design/CAD Symposium in 1995 and of the 1999 IEEE Workshop on Signal Processing Systems: Design and Implementation. He is the Past-Chair of Taipei Chapter of IEEE Circuits and Systems (CAS) Society, and is a member of the IEEE CAS Technical Committee of VLSI Systems and Applications, the Technical Committee of Visual Signal Processing and Communications, and the IEEE Signal Processing Technical Committee of Design and Implementation of SP Systems. He is the Chair-Elect of the IEEE CAS Technical Committee on Multimedia Systems and Applications, During 2001-2002, he served as a Distinguished Lecturer of the IEEE CAS Society. He received the Best Paper Award from the R.O.C. Computer Society in 1990 and 1994. Annually from 1991 to 1999, he received Long-Term (Acer) Paper Awards. In 1992, he received the Best Paper Award of the 1992 Asia-Pacific Conference on circuits and systems in the VLSI design track. In 1993, he received the Annual Paper Award of the Chinese Engineer Society. In 1996 and 2000, he received the Outstanding Research Award from the National Science Council, and in 2000, the Dragon Excellence Award from Acer. He is a member of Phi Tan Phi.     

A Programmable Parallel VLSI Architecture for 2-D Discrete Wavelet Transform

Many VLSI architectures for computing the discrete wavelet transform (DWT) were presented, but the parallel input data sequence and the programmability of the 2-D DWT were rarely mentioned. In this paper, we present a parallel-processing VLSI architecture to compute the programmable 2-D DWT, including various wavelet filter lengths and various wavelet transform levels. The proposed architecture is very regular and easy for extension. To eliminate high frequency components, the pixel values outside the boundary of the image are mirror-extended as the symmetric wavelet transform (SWT) and the mirror-extension is realized via the routing network. Owing to the property of the parallel processing, we adopt the row-based recursive pyramid algorithm (RPA), similar to 1-D RPA, as the data scheduling. This design has been implemented and fabricated in a 0.35 m 1P4M CMOS technology and the working frequency is 50 MHz. The chip size is about 5200 m × 2500 m. For a 256 × 256 image, the chip can perform 30 frames per second with the filter length varying from 2 to 20 and with various levels. The proposed architecture is suitable for real-time applications such as JPEG 2000.     

An Efficient VLSI Architecture for Computation of Discrete Fractional Fourier Transform

Since decades, the fractional Fourier transform (FrFT) has attracted researchers from various domains such as signal and image processing applications. These applications have been essentially demanding the requirement of low computational complexity of FrFT. In this paper, FrFT is simplified to reduce the complexity, and further an efficient CORDIC-based architecture for computing discrete fractional Fourier transform (DFrFT) is proposed which brings down the computational complexity and hardware requirements and provides the flexibility to change the user defined fractional angles to compute DFrFT on-the-fly. Architectural design and working method of proposed architecture along with its constituent blocks are discussed. The hardware complexity and throughput of the proposed architecture are illustrated as well. Finally, the architecture of DFrFT of the order sixteen is implemented using Verilog HDL and synthesized targeting an FPGA device ”XLV5LX110T”. The hardware simulation is performed for functional verification, which is compared with the MATLAB simulation results. Further, the physical implementation result of the proposed design shows that the design can be operated at a maximum frequency of 154 MHz with the latency of 63-clock cycles.     

Low-Power,Low-Complexity Bit-Serial VLSI Architecture for 1D Discrete Wavelet Transform

The discrete wavelet transform (DWT) is an upcoming compression technique that has been selected for MPEG-4 and JEPG 2000, because it has no blocking effects and it efficiently determines the frequency property of the temporary signals. In this paper, we propose a low-complexity, low-power bit-serial DWT architecture, employing a two-channel lattice-based quadrature mirror filter (QMF). The filter consists of four lattices (filter length = 8), and we determine the quantization bit for the coefficients using a fixed-length peak signal-to-noise ratio analysis and propose the architecture of the bit-serial multiplier with a fixed coefficient. The canonical signed digit encoding for the coefficients is applied to minimize the number of nonzero bits, thus reducing the hardware complexity. The proposed folded one-dimensional DWT architecture processes the other resolution levels during idle periods by decimations, and it provides efficient scheduling. The proposed architecture requires only flip-flops and full adders. This architecture has been designed and verified by the Verilog HDL and synthesized using the Synopsys Design Compiler with the DongbuAnam 0.18 μm Standard Cell Library. The maximum throughput is 393 Mbps at 450 MHz with a latency of 16 clocks, and the gate count is about 5K in equivalent two-input NAND gates. The dynamic power is 7.02 mW at 1.8 V. The data scheduling using a data dependency graph, and the performance, power, and required hardware cost are discussed.     

离散小波变换的VLSI实现

离散小波变换已广泛应用于信号处理中。然而,实时小波变换需要大量运算,因此,专用小波变换芯片的设计已成为信号处理中的关键技术。文章提出了一种小波变换递归金字塔算法的VLSI结构,采用一组输入延迟单元和一个控制单元,用一组并行滤波器完成了小波变换。编写了相应的Verilog HDL模块,并进行了仿真和逻辑综合。     

A Configurable Architecture for the Wavelet Packet Transform

The standard Wavelet Transform (WT) has a wide range of applications, from signal analysis to image or video compression and communications. Most of these applications would be benefited if the transform provided good spectral and temporal resolution in arbitrary regions of the time-frequency plane. This flexible choice of the time-frequency tiling is provided by the Wavelet Packet Transform (WPT). Though many VLSI architectures have been proposed for the WT in the literature, it is not the case for the WPT. We present both word-serial and word-parallel real-time pipelined architectures capable of computing a complete WPT binary tree, but which are easily configurable to compute any required WPT subtree.     

Adaptive Directional Lifting Wavelet Transform VLSI Architecture

Journal of Signal Processing Systems - This paper presents an efficient VLSI architecture of the 2-D wavelet transform for the adaptive directional lifting (ADL) scheme in image coding. To avoid...     

低功耗并行的提升式5/3二维离散小波变换的VLSI架构

离散小波变换需要较大的运算量和运算空间,为了提高JPEG2000图像压缩速度,提出一种基于提升算法的二维离散5/3小波变换的VLSI架构,这种结构同时进行行变换和列变换。文章对于VLSI架构的五大模块(行小波变换运算模块、两个列小波变换模块、FIFO寄存组和系统整体控制模块)的硬件实现给出了相应的方案。在Quartus II 7.2的平台下对于设计的该系统的时序仿真测试结果表明,综合分析后系统最小组合逻辑时延为7.142ns,可达到的最高频率为140.02MHz。时序仿真测试中当系统工作频率为100MHz,数据吞吐率达到773.944Mbit/s。     

二维离散小波变换的VLSI实现

小波变换图像编码获得了比传统DCT变换编码更好的图像质量和更高的压缩比,然而,实时二维小波变换需要大量运算,因此,专用小波变换芯片的设计已成为小波图像编码中的关键技术,文章提出了一种高速的二维小波变换的VLSI结构。根据模块化的设计思想,设计出一组二维小波变换的基本模块。通过将这些模块按变换要求适当组装,完成了多级二维小波变换,编写了相应的VerilogHDL模型,并进行了仿真和逻辑综合。     

Weighted Adaptive Lifting-Based Wavelet Transform for Image Coding

In this paper, a new weighted adaptive lifting (WAL)-based wavelet transform is presented. The proposed WAL approach is designed to solve the problems existing in the previous adaptive directional lifting (ADL) approach, such as mismatch between the predict and update steps, interpolation favoring only horizontal or vertical direction, and invariant interpolation filter coefficients for all images. The main contribution of the proposed approach consists of two parts: one is the improved weighted lifting, which maintains the consistency between the predict and update steps as far as possible and preserves the perfect reconstruction at the same time; another is the directional adaptive interpolation, which improves the orientation property of the interpolated image and adapts to statistical property of each image. Experimental results show that the proposed WAL-based wavelet transform for image coding outperforms the conventional lifting-based wavelet transform up to 3.06 dB in PSNR and significant improvement in subjective quality is also observed. Compared with the ADL-based wavelet transform, up to 1.22-dB improvement in PSNR is reported.