Optimization Design of Biorthogonal Wavelet Filter Banks for Extending JPEG 2000 Standard Part-2

A generic optimization design approach of biorthogonal wavelet filter banks (BWFB) for extending the JPEG 2000 standard part-2 is presented in this paper. This approach adopts Vaidyanathan optimal coding gain criterion to design the BWFB, and adopts peak signal-to-noise ratio (PSNR) as the criterion to optimize this BWFB. A functional relation between the general BWFB and their lifting scheme is derived in the first place with respect to one free variable, so that the optimization design of the BWFB is easier and more convenient. In addition, a general image model is formulated as a first-order Markov process driven by Gaussian white noise. It is taken as an input of two-channel filter banks which satisfy perfect reconstruction (PR) condition to realize subband coding for obtaining the optimal BWFB according to the Vaidyanathan optimal coding gain criterion. Finally, a new 9/7 BWFB with rational coefficients is proposed for extending the JPEG 2000 standard part-2, with PSNR of reconstructed images only 0.20 dB lower than standard CDF 9/7 BWFB for infrared thermal image compressions.     

A direct approach to the design of QMF banks via frequency domainoptimization

This paper studies the design of quadrature mirror filter (QMF) banks via frequency domain optimization. A direct approach is adopted that gives the necessary and sufficient condition for perfect reconstruction (PR). While analysis filter banks are designed to achieve frequency domain specifications required for subband coding, synthesis filter banks are designed to minimize the reconstruction error in frequency domain. The criterion used to measure the reconstruction error is H_∞ or Chebyshev norm (sup-norm). State-space solutions are derived for the H_∞ optimization, and numerical algorithms are developed to obtain the optimal synthesis filter bank. Moreover, the asymptotic PR property is established for optimal H_∞ solution of the synthesis filter bank     

Design of NPR DFT-Modulated Filter Banks via Iterative Updating Algorithm

In this paper, an efficient algorithm is proposed to design nearly-perfect-reconstruction (NPR) DFT-modulated filter banks. First, the perfect-reconstruction (PR) condition of the oversampled DFT-modulated filter banks in the frequency domain is transformed into a set of quadratic equations with respect to the prototype filter (PF) in the time domain. Second, the design problem is formulated as an unconstrained optimization problem that involves PR condition and stopband energy of the PF. With the gradient vector of the objective function, an efficient iterative algorithm is presented to design the PF, which is updated with linear matrix equations at each iteration. The algorithm is identified as a modified Newton’s method, and its convergence is proved. Numerical examples and comparison with many other existing methods are included to demonstrate the effectiveness of the proposed method.     

一类冗余比为2的二维DFT调制滤波器组的设计

本文构建了一类冗余比为2的二维线性相位的双原型离散傅立叶变换（DFT）调制滤波器组。利用原型滤波器的多相位分解,推导出了该滤波器组的完全重构(PR)条件。基于该PR条件,我们将滤波器组的设计归结为一个关于原型滤波器的多相位分量的无约束优化问题。由于原型滤波器是线性相位的,多相位分量之间具有一定的关系,因此我们可以简化该优化问题。仿真结果验证了滤波器组PR条件的正确性。同时,仿真表明了优化算法的有效性,设计所得的滤波器组重构误差很小、频率特性较好,基本满足实际应用的需要。      

用提升方法设计M带LPPR-FIR滤波器组

 本文研究了如何用提升方法构造M带PR-FIR滤波器组,并且考虑了一种特殊情形的线性相位(Linear Phase,LP)性质,及其优化设计问题,即如何转化为一个二次型优化问题.     

用提升方法设计M带LPPR-R滤波器组

本文研究了如何用提升方法构造M带PR-FIR滤波器组,并且考虑了一种特殊情形的线性相位(LinearPhase,LP)性质,及其优化设计问题,即如何转化为一个二次型优化问题.     

一种基于遗传算法的混合滤波器组设计方法

针对可满足近似完全重构的双通道混合滤波器组,其中高阶数的模拟滤波器一般不容易设计优化。采用遗传算法设计5阶模拟分解滤波器,并基于逆快速傅里叶变换实现数字综合滤波器的设计优化以滤除掉镜像频谱,保证近似完全重构。文中设计了由5阶模拟分解滤波器和32阶数字综合滤波器组成的混合滤波器组,仿真结果表明:可以实现的最大失真误差为4.761 8×10-11dB,平均失真误差为-9.2×10-14dB,最大混叠误差为-154 dB,平均混叠误差为-200 dB,可满足24 bits的模数转换器系统的要求。     

用lifting方法设计最优LPPR-FIR滤波器组

该文研究了如何用lifting方法构造线性相位完全重建有限脉冲响应(LPPR-FIR)滤波器组的优化设计问题,即如何转化为一个二次型优化问题.然后把该方法推广到M带FIR滤波器组,考虑在一种特殊情形中如何构造具有线性相位性质的M带PR-FIR滤波器组,最后列举了几个例子说明如何用lifting方法构造M带LPPR-FIR滤波器组。     

Design of linear phase M-channel perfect reconstruction FIR filterbanks

We propose two approaches to design M channel nonparaunitary filter banks that satisfy perfect reconstruction (PR) and linear phase (LP) properties. In the first approach, the PR condition is imposed on only a high-pass filter. Although this method does not require nonlinear optimization, it has a demerit in that the order of a high-pass filter becomes high. In the second approach, two filters are optimized simultaneously using a Lagrange-Newton method. We can design PR filter banks that have the same length. The PR constraint is also formulated as a linear and nonlinear equation of the analysis filter coefficients. Finally, some design examples are included     

Design of IIR orthogonal wavelet filter banks using lifting scheme

The lifting scheme is well known to be an efficient tool for constructing second generation wavelets and is often used to design a class of biorthogonal wavelet filter banks. For its efficiency, the lifting implementation has been adopted in the international standard JPEG2000. It is known that the orthogonality of wavelets is an important property for many applications. This paper presents how to implement a class of infinite-impulse-response (IIR) orthogonal wavelet filter banks by using the lifting scheme with two lifting steps. It is shown that a class of IIR orthogonal wavelet filter banks can be realized by using allpass filters in the lifting steps. Then, the design of the proposed IIR orthogonal wavelet filter banks is discussed. The designed IIR orthogonal wavelet filter banks have approximately linear phase responses. Finally, the proposed IIR orthogonal wavelet filter banks are applied to the image compression, and then the coding performance of the proposed IIR filter banks is evaluated and compared with the conventional wavelet transforms.     

An integrated framework for adaptive subband image coding

Previous work on filter banks and related expansions has revealed an interesting insight: different filter bank trees can be regarded as different ways of constructing orthonormal bases for linear signal expansion. In particular, fast algorithms for finding best bases in an operational rate-distortion (R/D) sense have been successfully used in image coding. Independently of this work, other research has also explored the design of filter banks that optimize energy compaction for a single signal or a class of signals. In this paper, we integrate these two different but complementary approaches to best-basis design and propose a coding paradigm in which subband filters, tree structure, and quantizers are chosen to optimize the R/D performance. These coder attributes represent side information. They are selected from a codebook designed off-line from training data, using R/D as the design criterion. This approach provides a rational framework in which to explore alternatives to empirical design of filter banks, quantizers, and other coding parameters. The on-line coding algorithm is a relatively simple extension of current R/D-optimal coding algorithms that operate with fixed filter banks and empirically designed quantizer codebooks. In particular, it is shown that selection of the best adapted filter bank from the codebook is computationally elementary     

一种新型伪镜像滤波器组的实现方法

本文提出了一种新型２Ｍ个通道伪镜像滤波器组的结构和设计方法。本设计方法中，低通原型滤波器采用两级级联线性相位ＦＩＲ的结构，并使得整个分析／综合系统性能近于全恢复，无群时延失真。应用此方法设计伪镜像滤波器组，分析和综合滤波器组的结构和设计方法都比较简单，算法效率高，实现比较容易，这类滤波器组可用于语音的子带编码等。本文最后给出了一个实例。     

Optimal design of high-performance separable wavelet filter banks for image coding

An optimization-based method is proposed for the design of high-performance separable wavelet filter banks for image coding. This method yields linear-phase perfect-reconstruction systems with high coding gain, good frequency selectivity, and certain prescribed vanishing-moment properties. Several filter banks designed with the proposed method are presented and shown to work extremely well for image coding, outperforming the well-known 9/7 filter bank from JPEG 2000 in most cases. With the proposed design method, the coding gain can be maximized with respect to the separable or isotropic image model, or jointly with respect to both models. The joint case, which is shown to be equivalent to the isotropic case, is experimentally demonstrated to lead to filter banks with better average coding performance than the separable case.During the development of the proposed design method, filter banks from a certain popular separable two-dimensional (2D) wavelet class (to which our optimal designs belong) were observed to always have a higher coding gain with respect to the separable image model than with respect to the isotropic one. This behavior is examined in detail, leading to the conclusion that, for filter banks belonging to the above class, it is highly improbable (if not impossible) for the isotropic coding gain to exceed the separable coding gain.     

Design and Factorization of Two-Channel Perfect Reconstruction Filter Banks with Causal-Stable IIR Filters

In this paper, new design and factorization methods of two-channel perfect reconstruction (PR) filter banks (FBs) with casual-stable IIR filters are introduced. The polyphase components of the analysis filters are assumed to have an identical denominator in order to simplify the PR condition. A modified model reduction is employed to derive a nearly PR causal-stable IIR FB as the initial guess to obtain a PR IIR FB from a PR FIR FB. To obtain high quality PR FIR FBs for carrying out model reduction, cosine-rolloff FIR filters are used as the initial guess to a nonlinear optimization software for solving to the PR solution. A factorization based on the lifting scheme is proposed to convert the IIR FB so obtained to a structurally PR system. The arithmetic complexity of this FB, after factorization, can be reduced asymptotically by a factor of two. Multiplier-less IIR FB can be obtained by replacing the lifting coefficients with the canonical signal digitals (CSD) or sum of powers of two (SOPOT) coefficients.     

无约束法设计完全重构M带滤波器组

本文提出了一种新的正交和双正交完全重构M带滤波器组的设计方法.这种方法是建立在多项式分解基础之上,可在无约束条件下设计,所设计的滤波器组具有结构化完全重构特点,对于双正交滤波器组还可以方便设计系统时延.和已有的方法相比,新方法具有低设计复杂度特点.文中还描述了设计过程,最后给出了设计例子和结果.     

Design of 2D oversampled linear phase DFT modulated filter banks via modified Newton's method

In this paper, the structure of the 2D oversampled DFT modulated filter banks is analyzed and a spatial-domain condition of a filter bank without transfer function distortion is derived. Based upon the spatial-domain condition, a modified Newton's method is presented for fast design of 2D oversampled linear phase (LP) DFT modulated filter banks with nearly perfect reconstruction (NPR). We formulate the design problem into an unconstrained optimization with a fourth-order objective function, which is the weighted sum of the transfer function distortion of the filter bank and the stopband energy of the prototype filter (PF). The optimization is solved by the modified Newton's method, where each of iterations updates the PF by a set of linear equations. It is proved that the iteration process fast converges to a stationary point of the objective function. Compared with the existing methods, the new method is fast in computation and can design 2D filter banks with a large number of subbands.     

Recursive biorthogonal interpolating wavelets and signal-adaptedinterpolating filter banks

In this paper, by combining the ideas of the recursive wavelets with second-generation wavelets, a family of recursive biorthogonal interpolating wavelets (RBIWs) is developed. The RBIWs have simple shape parameter vectors on each level, which allows a multichannel decomposition algorithm and provides, a flexible structure for designing signal-adapted interpolating filter banks. In the single-level case, an efficient approach to design an optimum two-channel biorthogonal interpolating filter bank is proposed, which maximizes the coding gain under the traditional quantization noise assumption. Furthermore, in the multilevel case, using level-wise optimization of the shape parameter vectors, signal-adapted tree-structured recursive biorthogonal interpolating filter banks (RBIFBs) are designed, which are efficient in computation and can remarkedly improve the coding gain. Finally, numerical results demonstrate the effectiveness of the proposed methods     

Design of Time–Frequency Localized Filter Banks: Transforming Non-convex Problem into Convex Via Semidefinite Relaxation Technique

We present a method for designing optimal biorthogonal wavelet filter banks (FBs). Joint time–frequency localization of the filters has been chosen as the optimality criterion. The design of filter banks has been cast as a constrained optimization problem. We design the filter either with the objective of minimizing its frequency spread (variance) subject to the constraint of prescribed time spread or with the objective of minimizing the time spread subject to the fixed frequency spread. The optimization problems considered are inherently non-convex quadratic constrained optimization problems. The non-convex optimization problems have been transformed into convex semidefinite programs (SDPs) employing the semidefinite relaxation technique. The regularity constraints have also been incorporated along with perfect reconstruction constraints in the optimization problem. In certain cases, the relaxed SDPs are found to be tight. The zero duality gap leads to the global optimal solutions. The design examples demonstrate that reasonably smooth wavelets can be designed from the proposed filter banks. The optimal filter banks have been compared with popular filter banks such as Cohen–Daubechies–Feauveau biorthogonal wavelet FBs, time–frequency optimized half-band pair FBs and maximally flat half-band pair FBs. The performance of optimal filter banks has been found better in terms of joint time–frequency localization.     

Genetic Algorithm-based Adaptive Optimization for Target Tracking in Wireless Sensor Networks

In this paper, we address the problem of genetic algorithm optimization for jointly selecting the best group of candidate sensors and optimizing the quantization for target tracking in wireless sensor networks. We focus on a more challenging problem of how to effectively utilize quantized sensor measurement for target tracking in sensor networks by considering best group of candidate sensors selection problem. The main objective of this paper is twofold. Firstly, the quantization level and the group of candidate sensors selection are to be optimized in order to provide the required data of the target and to balance the energy dissipation in the wireless sensor network. Secondly, the target position is to be estimated using quantized variational filtering (QVF) algorithm. The optimization of quantization and sensor selection are based on the Fast and Elitist Multi-objective Genetic Algorithm (NSGA-II). The proposed multi-objective (MO) function defines the main parameters that may influence the relevance of the participation in cooperation for target tracking and the transmitting power between one sensor and the cluster head (CH). The proposed algorithm is designed to: i) avoid the problem lot of computing times and operation counts, and ii) reduce the communication cost and the estimation error, which leads to a significant reduction of energy consumption and an accurate target tracking. The computation of these criteria is based on the predictive information provided by the QVF algorithm. The simulation results show that the NSGA-II -based QVF algorithm outperforms the standard quantized variational filtering algorithm and the centralized quantized particle filter.     

近似完全重构IIR余弦调制滤波器组的优化设计

提出一种新的近似完全重构因果稳定的IIR余弦调制滤波器组的设计方法。基于预先给定的极点值,IIR原型滤波器的设计问题可以简化成一个凸极大值极小化的优化问题,从而采用二阶锥规划法求解。所得余弦调制滤波器组具有良好的频率特性和合理的完全重构误差。所设计的原型滤波器是因果稳定的,并且其多相因子分母相同,简化了完全重构条件,可以用来进一步优化得到的完全重构系统。