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Construction of parametric biorthogonal wavelet filter banks with two parameters for image coding

机译:具有两个参数的参数双正交小波滤波器组的构造

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We had presented a simple technique, which is based on the theory of Diophantine equation, for parametri-zation of popular biorthogonal wavelet filter banks (BWFBs) having the linear phase and arbitrary multiplicity of vanishing moments (VMs), and constructed a type of parametric BWFBs with one free parameter [15]. Here we generalize this technique to the case of two parameters, and construct a type of parametric BWFBs with two free parameters. The closed-form parameter expressions of the BWFBs are derived, with which any two-parameter family of BWFBs having preassigned VMs can be constructed, and six families, i.e., 9/11, 10/10, 13/11, 10/14, 17/11, and 10/18 families, are considered here. Two parameters provide two degrees of freedom to optimize the resulting BWFBs with respect to other criteria. In particular, in each family, three specific rational-coefficient BWFBs with attractive features are obtained by adjusting the parameters: the first is not only very close to a quadrature mirror filter (QMF) bank, but has optimum coding gain; the second possesses characteristics that are close to the irrational BWFB with maximum VMs by Cohen et al.; and the last which has binary coefficients can realize a multiplication-free discrete wavelet transform. In addition, two BWFBs are systematically verified to exhibit performance competitive to several state-of-the-art BWFBsrnfor image compression, and yet require lower computationalrncosts.
机译:我们已经提出了一种简单的技术,该技术基于Diophantine方程理论,用于对具有线性相位和消失矩(VM)任意多重的流行双正交小波滤波器组(BWFB)进行参数化,并构造了一种参数化方法具有一个自由参数的BWFB [15]。在这里,我们将这种技术推广到两个参数的情况,并构造具有两个自由参数的参数化BWFB。导出BWFB的闭式参数表达式,可以构造具有预先分配的VM的BWFB的任何两参数族,以及六个族,即9 / 11、10 / 10、13 / 11、10 / 14,这里考虑了17/11和10/18家庭。两个参数提供了两个自由度,可以相对于其他标准优化生成的BWFB。特别是,在每个系列中,通过调整参数都可以得到三个具有吸引力的特定有理系数BWFB:第一个不仅非常接近正交镜滤波器(QMF)库,而且具有最佳的编码增益;第二种具有与Cohen等人的最大VM接近的非理性BWFB的特征。具有二进制系数的最后一个可以实现无乘法离散小波变换。另外,两个BWFB经过系统验证,表现出与几种最新BWFB图像压缩竞争的性能,但所需的计算成本却较低。

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