Design of Low-Complexity High-Performance Wavelet Filters for Image Analysis

Naik, Ameya K.; Holambe, Raghunath S.

doi:10.1109/tip.2013.2237917

Cited by 23 publications

(5 citation statements)

References 33 publications

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“…The article focuses on such a design approach to construct integer and dyadic wavelets for image compression applications. This paper is an extension of the work presented in [8]. Whereas WCHP (Wavelets Constructed using Halfband Polynomial) ensures maximum vanishing moments, they may not be necessarily dyadic.…”

Section: Related Workmentioning

confidence: 94%

“…It is well known that the CDF 9/7 filters have irrational coefficients and thus require floating point arithmetic. The problems associated with the floating point implementation of filters and the associated higher complexity has been addressed in [8]- [11]. Complexity reduction can be achieved by designing filters that have rational coefficients with preferably dyadic values.…”

Section: Related Workmentioning

confidence: 99%

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New Approach to the Design of Low Complexity 9/7 Tap Wavelet Filters With Maximum Vanishing Moments

Naik

Holambe

2014

IEEE Trans. on Image Process.

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In this paper, we present a novel approach for the design of 9/7 near-perfect-reconstruction wavelets that are efficient for image compression. These wavelets have maximum vanishing moments for both decomposition and reconstruction filters. Among the existing 9/7 tap wavelet filters, the Cohen-Daubechies-Feauveau (CDF) 9/7 are known to have the largest regularity. However, these wavelets have irrational coefficients thus requiring infinite precision implementation. Unlike state- of-art designs that compromise vanishing moments for attaining low-complexity coefficients, our algorithm ensures both. We start with a spline function of length 5 and select the remaining factors to obtain wavelets with rationalized coefficients. By proper choice of design parameters, it is possible to find very low complexity dyadic wavelets with compact support.We suggest a near half band criterion to attain a suitable combination of low-pass analysis and decomposition filters. The designed filter bank is found to give significant hardware advantage as compared with existing filter pairs. Moreover, these low-complexity wavelets have characteristics similar to standard (CDF 9/7) wavelets. The designed wavelets are tested for their suitability in applications such as image compression. Simulations results depict that the designed wavelets give comparable performances on most of the benchmark images. Subsequently, they can be used in applications that require fewer computations and lesser hardware.

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Section: Related Workmentioning

confidence: 94%

Section: Related Workmentioning

confidence: 99%

New Approach to the Design of Low Complexity 9/7 Tap Wavelet Filters With Maximum Vanishing Moments

Naik

Holambe

2014

IEEE Trans. on Image Process.

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“…Triplet half-band filter bank (THFB) has been presented by Rahulkar and Holambe [15], where the authors found out the coefficients are irrational numbers, which is difficult to implement on hardware. Further, Naik and Holambe [16] have designed low complexity wavelet filter banks. Anbarjafari et al [17] have obtained high resolution satellite image with the help of dual tree complex wavelet transform from noisy, blurred, and undersampled low resolution images.…”

Section: Banksmentioning

confidence: 99%

Image Resolution Enhancement of Satellite Images Using Dyadic Integer Coefficient Wavelet Filter for Wavelet Transform

Chopade¹

2021

ITII

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In this paper, image resolution enhancements for satellite images are proposed using dyadic integer coefficients based wavelet filter (DICWF). We proposes a technique in which discrete wavelet transform and stationary wavelet transform using DICWF which is used to obtain a high resolution image and this image is derived from frequency subbands. The satellite images play a very vital role now days in the development of technical aspects which needs to be enhanced. These satellite images are superresolved with the help of dyadic integer coefficient-based wavelet filters, which reduces the hardware complexity and computational difficulties due to the rational and integer coefficients of these filter banks. The value of the peak signal-to-noise ratio (PSNR) of the proposed method and the resultant visual images of the proposed method show the effectiveness of this algorithm over other existing algorithms using discrete wavelet transform. Noise can be minimized by applying thresholding on different frequency subbands which obtained by the application of DICWF to the noisy, blurred input images.

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“…Let us assume that all samples have the same order of magnitude, then, the difference between and can be large due to the shift operation. This idea can be exploited to predict the probability of the th carry signal to be "1": (13) For some of the values taken by , if and is "small," then (14) The condition in (14) applied to (13) leads to (15) with…”

Section: B Probability-based Thresholdingmentioning

confidence: 99%

“…As an example in [6], [7] the B-spline factorization [8], [9] is exploited to design multiplierless FB architectures. Recently, other approaches have been proposed as well, e.g., algebraic integer quantization [10], [11], coefficient rationalization [12], polymorphic implementation [13], and half-band polynomial factorization [14].…”

Section: Introductionmentioning

confidence: 99%

Result-Biased Distributed-Arithmetic-Based Filter Architectures for Approximately Computing the DWT

Martina

Masera

Roch

et al. 2015

IEEE Trans. Circuits Syst. I

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The discrete wavelet transform is a fundamental block in several schemes for image compression. Its implementation relies on filters that usually require multiplications leading to a relevant hardware complexity. Distributed arithmetic is a general and effective technique to implement multiplierless filters and has been exploited in the past to implement the discrete wavelet transform as well. This work proposes a general method to implement a discrete wavelet transform architecture based on distributed arithmetic to produce approximate results. The novelty of the proposed method relies on the use of result-biasing techniques (inspired by the ones used in fixed-width multiplier architectures), which cause a very small loss of quality of the compressed image (average loss of 0.11 dB and 0.20 dB in terms of PSNR for the 9/7 and 10/18 wavelet filters, respectively). Compared with previously proposed distributed-arithmetic-based architectures for the computation of the discrete wavelet transform, this technique saves from about 20% to 25% of hardware complexity.

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Design of Low-Complexity High-Performance Wavelet Filters for Image Analysis

Cited by 23 publications

References 33 publications

New Approach to the Design of Low Complexity 9/7 Tap Wavelet Filters With Maximum Vanishing Moments

New Approach to the Design of Low Complexity 9/7 Tap Wavelet Filters With Maximum Vanishing Moments

Image Resolution Enhancement of Satellite Images Using Dyadic Integer Coefficient Wavelet Filter for Wavelet Transform

Result-Biased Distributed-Arithmetic-Based Filter Architectures for Approximately Computing the DWT

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