A fast Discrete Wavelet Transform algorithm for visual processing applications

Hsia, Chih-Hsien; Guo, Jing-Ming; Chiang, Jen‐Shiun

doi:10.1016/j.sigpro.2011.06.009

Cited by 26 publications

(12 citation statements)

References 17 publications

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“…From the results in the Table, it can be seen that the ME-SMDWT (Eqs. (14), (16), (18), (20)) obtained from this research indeed exhibits the same performance as the LDWT; However, its complexity is lower, while the operational efficiency is higher.…”

Section: Performance Comparison Between Me-smdwt and Ldwtsupporting

confidence: 55%

“…In [13,14], presented the symmetry of the mask coefficients of SMDWT, and the symmetry of the coefficients of the mask filters of four subbands is shown in Fig. 5.…”

Section: Basic Concepts Of Smdwtmentioning

confidence: 99%

“…According to the previously mentioned particle encoding principle, the corresponding shift-and-add based circuit architecture should be as shown in (14).…”

Section: Hardware Architecture Of a Me-smdwtmentioning

confidence: 99%

“…In order to solve the problems of the large temporary memory capacities and high critical paths required for traditional 2D DWT, Hsia et al [13,14] proposed a method called Symmetric Mask-based DWT (SMDWT), which uses a symmetric mask-based scheme to process an integer Lifting-based DWT (LDWT). In that method, after image inputting, it only takes the operations of mask filters of different subbands to implement spatial filtering tasks, and the computational complexity of the generated LL-band image is only about 1.6 % of that of a Daubechies DWT.…”

Section: Introductionmentioning

confidence: 99%

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Evolutionary design of multiplierless lifting-based 2D DWT filters for low-resolution image processing

Chen¹,

Hsia

Yang³

2015

Multimed Tools Appl

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The most difficult challenge in developing a high-efficiency embedded image processing system relates to how to execute complicated Digital Signal Processing (DSP) algorithm with embedded processor, especially when processing high-resolution images. A whole system may start to run very slowly because of the large volumes of data being processed and the complexity of the algorithm, rendering it unable to achieve real-time processing. Executing motion detection in low-resolution image was already proved to be able to reduce the loading of data manipulation and to be able to help filter out noise and fake motion. However, smoothing filter pointed out in the work will affect the quality of image. Although the LL-band signal of a 2D Discrete Wavelet Transform (DWT) domain can retain the main part of the energy and information of the original image, a complex algorithm is more suitable for the application of a low-pass filter. Symmetric Mask-based DWT (SMDWT) has the advantage of reduced complexity, regular signal coding, and independent subband coding processing. In this paper, we use a Particle Swarm Optimization (PSO) approach to automatically evolve the multiplierless 2D SMDWT filters hardware architecture. The architecture employs only shift-and-addition operations to replace the complex floating-point multiplication and division operations. It can use shift-and-add based SMDWT filter to decompose a low-resolution image and do real-time image processing system design with low-resolution image processing technique.

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Section: Performance Comparison Between Me-smdwt and Ldwtsupporting

confidence: 55%

“…In [13,14], presented the symmetry of the mask coefficients of SMDWT, and the symmetry of the coefficients of the mask filters of four subbands is shown in Fig. 5.…”

Section: Basic Concepts Of Smdwtmentioning

confidence: 99%

“…According to the previously mentioned particle encoding principle, the corresponding shift-and-add based circuit architecture should be as shown in (14).…”

Section: Hardware Architecture Of a Me-smdwtmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evolutionary design of multiplierless lifting-based 2D DWT filters for low-resolution image processing

Chen¹,

Hsia

Yang³

2015

Multimed Tools Appl

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show abstract

“…DWT, a multi-resolution decomposition for input data, has been widely used in signal processing, image compression, denoising and so on [42].…”

Section: A Matrix Compression Technique Using Dwt Approximationmentioning

confidence: 99%

A level set method for topological shape optimization of 3D structures with extrusion constraints

Gao

et al. 2015

Computer Methods in Applied Mechanics and Engineering

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A new discrete wavelet transform appropriate for hardware implementation

Meshkat

Dehghani

2020

Circuit Theory & Apps

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Summary A new method for computation of discrete wavelet transform is introduced. The impulse response of the finite impulse response (FIR) filter, as the main block in filter bank method, is realized such that orthonormal wavelet transform is achieved without using any multiplier as the most challenging part of the FIR filters. It is proved that the calculated Sobolev regularity of the proposed wavelet is higher than that of Daubechies for the same support width. Compared with most popular known wavelets, simulation results of the newly introduced wavelet for signal denoising prove remarkable advantage of our wavelet especially in terms of complexity and power consumption. The proposed wavelet and well‐known Daubechies wavelet are separately implemented on the Spartan‐6 FPGA (Field Programmable Gate Array) to compare the performance of them. The occupied slices and LUTs (Lookup Table) in realization of the proposed wavelet in comparison with those of Daubechies wavelet are decreased by 50% and 56%, respectively. Its power consumption at 100 MHz is also reduced by 86% in comparison with the Daubechies wavelet, and maximum frequency is increased by 186%. Implementation with standard cells of a 0.18‐μm CMOS (Complementary Metal Oxide Semiconductor Field Effect Transistor) technology shows 75% and 85% reduction in the power and chip area, respectively.

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A fast Discrete Wavelet Transform algorithm for visual processing applications

Cited by 26 publications

References 17 publications

Evolutionary design of multiplierless lifting-based 2D DWT filters for low-resolution image processing

Evolutionary design of multiplierless lifting-based 2D DWT filters for low-resolution image processing

A level set method for topological shape optimization of 3D structures with extrusion constraints

A new discrete wavelet transform appropriate for hardware implementation

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