235 research outputs found

    A VLSI architecture of JPEG2000 encoder

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    Copyright @ 2004 IEEEThis paper proposes a VLSI architecture of JPEG2000 encoder, which functionally consists of two parts: discrete wavelet transform (DWT) and embedded block coding with optimized truncation (EBCOT). For DWT, a spatial combinative lifting algorithm (SCLA)-based scheme with both 5/3 reversible and 9/7 irreversible filters is adopted to reduce 50% and 42% multiplication computations, respectively, compared with the conventional lifting-based implementation (LBI). For EBCOT, a dynamic memory control (DMC) strategy of Tier-1 encoding is adopted to reduce 60% scale of the on-chip wavelet coefficient storage and a subband parallel-processing method is employed to speed up the EBCOT context formation (CF) process; an architecture of Tier-2 encoding is presented to reduce the scale of on-chip bitstream buffering from full-tile size down to three-code-block size and considerably eliminate the iterations of the rate-distortion (RD) truncation.This work was supported in part by the China National High Technologies Research Program (863) under Grant 2002AA1Z142

    Development of Lifting-based VLSI Architectures for Two-Dimensional Discrete Wavelet Transform

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    Two-dimensional discrete wavelet transform (2-D DWT) has evolved as an essential part of a modem compression system. It offers superior compression with good image quality and overcomes disadvantage of the discrete cosine transform, which suffers from blocks artifacts that reduces the quality of the inage. The amount of computations involve in 2-D DWT is enormous and cannot be processed by generalpurpose processors when real-time processing is required. Th·"efore, high speed and low power VLSI architecture that computes 2-D DWT effectively is needed. In this research, several VLSI architectures have been developed that meets real-time requirements for 2-D DWT applications. This research iaitially started off by implementing a software simulation program that decorrelates the original image and reconstructs the original image from the decorrelated image. Then, based on the information gained from implementing the simulation program, a new approach for designing lifting-based VLSI architectures for 2-D forward DWT is introduced. As a result, two high performance VLSI architectures that perform 2-D DWT for 5/3 and 9/7 filters are developed based on overlapped and nonoverlapped scan methods. Then, the intermediate architecture is developed, which aim a·: reducing the power consumption of the overlapped areas without using the expensive line buffer. In order to best meet real-time applications of 2-D DWT with demanding requirements in terms of speed and throughput parallelism is explored. The single pipelined intermediate and overlapped architectures are extended to 2-, 3-, and 4-parallel architectures to achieve speed factors of 2, 3, and 4, respectively. To further demonstrate the effectiveness of the approach single and para.llel VLSI architectures for 2-D inverse discrete wavelet transform (2-D IDWT) are developed. Furthermore, 2-D DWT memory architectures, which have been overlooked in the literature, are also developed. Finally, to show the architectural models developed for 2-D DWT are simple to control, the control algorithms for 4-parallel architecture based on the first scan method is developed. To validate architectures develcped in this work five architectures are implemented and simulated on Altera FPGA. In compliance with the terms of the Copyright Act 1987 and the IP Policy of the university, the copyright of this thesis has been reassigned by the author to the legal entity of the university, Institute of Technology PETRONAS Sdn bhd. Due acknowledgement shall always be made of the use of any material contained in, or derived from, this thesis

    Fast Implementation of Lifting Based DWT Architecture For Image Compression

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    Technological growth in semiconductor industry have led to unprecedented demand for faster area efficient and low power VLSI circuits for complex image processing applications DWT-IDWT is one of the most popular IP that is used for image transformation In this work a high speed low power DWT IDWT architecture is designed and implemented on ASIC using 130nm Technology 2D DWT architecture based on lifting scheme architecture uses multipliers and adders thus consuming power This paper addresses power reduction in multiplier by proposing a modified algorithm for BZFAD multiplier The proposed BZFAD multiplier is 65 faster and occupies 44 less area compared with the generic multipliers The DWT architecture designed based on modified BZFAD multiplier achieves 35 less power reduction and operates at frequency of 200MHz with latency of 1536 clock cycles for 512x512 image The developed DWT can be used as an IP for VLSI implementatio

    Discrete Wavelet Transform Core for Image Processing Applications

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    This paper presents a flexible hardware architecture for performing the Discrete Wavelet Transform (DWT) on a digital image. The proposed architecture uses a variation of the lifting scheme technique and provides advantages that include small memory requirements, fixed-point arithmetic implementation, and a small number of arithmetic computations. The DWT core may be used for image processing operations, such as denoising and image compression. For example, the JPEG2000 still image compression standard uses the Cohen-Daubechies-Favreau (CDF) 5/3 and CDF 9/7 DWT for lossless and lossy image compression respectively. Simple wavelet image denoising techniques resulted in improved images up to 27 dB PSNR. The DWT core is modeled using MATLAB and VHDL. The VHDL model is synthesized to a Xilinx FPGA to demonstrate hardware functionality. The CDF 5/3 and CDF 9/7 versions of the DWT are both modeled and used as comparisons. The execution time for performing both DWTs is nearly identical at approximately 14 clock cycles per image pixel for one level of DWT decomposition. The hardware area generated for the CDF 5/3 is around 15,000 gates using only 5% of the Xilinx FPGA hardware area, at 2.185 MHz max clock speed and 24 mW power consumption
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