3-D adaptive digital signal processing for video signal

视频信号的 3D 自适应数字信号处理

• 批准号: 08650419
• 负责人: KAWAMATA Masayuki
• 金额: $ 1.41万
• 依托单位: Tohoku University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 1996
• 资助国家: 日本
• 起止时间: 1996 至 1998
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-08650419/
• 关键词: Multidimensional digital filters; 3-D signal processing; video signal processing; adaptive digital filters; 適応フィルタ

1. This research first proposes a bias removal algorithm for equation error-based 2-D adaptive cascade IIR filters with separable denominator function. As well known, equation error-based adaptive IIR filtering algorithms have the advantages of fast convergence and unimodal mean-square-error surface. However, they converge to biased parameter estimates in the presence of measurement noise. To handle the bias problem, the proposed algorithm uses a scaled value of the output error of each of the cascade sections as an estimate for the additive noise embedded in the signal part of the update procedure of the corresponding section. Thus, while maintaining the good convergence properties of equation error IIR filters, the effect of the measurement noise is suppressed. Input-output stability analysis is carried out, and the constraints required to maintain stability are derived.2. This research secondly considered the steady state mean square error (MSE) analysis for 2-D LMS adaptive filtering algorithm in which the filter's weights are updated along both vertical and horizontal directions as a doubly-indexed dynamical system. The MSE analysis is conducted using the well-known independence assumption. First we show that computation of the weight-error covariance matrix for doubly-indexed 2-D LMS algorithm requires an approximation for the weight-error correlation coefficients at large spatial lags. Then we propose a method to solve this problem. Further discussion is carried out for the special case when the input signal is white Gaussian. It is shown that the convergence in the MSE sense occurs for step size range that is significantly smaller than the one necessary for the convergence of the mean.

1.本研究首先提出一种基于方程误差的具有可分离分母函数的二维自适应级联IIR滤波器的偏置消除算法。众所周知，基于方程误差的自适应IIR滤波算法具有收敛速度快、均方误差曲面为单峰的优点。然而，他们收敛到有偏的参数估计存在测量噪声。为了处理偏差问题，所提出的算法使用每个级联部分的输出误差的缩放值作为对嵌入在相应部分的更新过程的信号部分中的加性噪声的估计。因此，在保持方程误差IIR滤波器的良好收敛特性的同时，抑制了测量噪声的影响。对系统进行了输入输出稳定性分析，推导了系统保持稳定所需的约束条件.其次，将滤波器权值沿水平和垂直方向沿着同时更新的二维LMS自适应滤波算法作为一个双指标动态系统进行稳态均方误差分析。MSE分析使用众所周知的独立性假设进行。首先，我们表明，双索引2-D LMS算法的加权误差协方差矩阵的计算需要在大的空间滞后的加权误差相关系数的近似。然后，我们提出了一种方法来解决这个问题。对输入信号为白色高斯分布的特殊情况进行了进一步的讨论。它示出的MSE意义上的收敛发生的步长范围是显着小于一个必要的平均值的收敛。

项目成果

Maha Shadaydeh,Masayuki Kawamata: "BIAS REMOVAL ALGORITHM FOR 2-D EQUATION ERROR ADAPTIVE IIR FILTERS"Proc.of IEEE International Workshop on Intelligent Signal Processing and Communication Systems. S16.3.1 S 16.3.6 (1997)

Maha Shadaydeh、Masayuki Kawamata：“二维方程误差自适应 IIR 滤波器的偏差消除算法”Proc.of IEEE 国际智能信号处理和通信系统研讨会。

Maha Shadaydeh,Masayuki Kawamata: "Convergence Analysis of Two-Dimensional LMS FIR Filters"Conference Record of the Thirty-First Asilomar Conference on Signals,Systems,and Computers. 348-353 (1997)

Maha Shadaydeh、Masayuki Kawamata：《二维 LMS FIR 滤波器的收敛性分析》第三十一届阿西洛玛信号、系统和计算机会议会议记录。

Maha Shadaydeh, Masayuki Kawamata: "Convergence Analysis of Tow-Dlmensional LMS FIR Filters" 31st Asilomar Conference on Signal,Systems,& Computers. 1-6 (1997)

Maha Shadaydeh、Masayuki Kawamata：“二维 LMS FIR 滤波器的收敛分析”第 31 届阿西洛玛信号、系统会议

高橋秀也,川又政征,樋口龍雄: "2次元LMSアルゴリズムに関する考察" 電気関係学会東北支部連合大会講演論文集. 319- (1996)

Hideya Takahashi、Masayuki Kawamata、Tatsuo Higuchi：“关于二维 LMS 算法的考虑”电气工程学会东北分会会议记录 319-（1996）。

Maha Shadaydeh,Masayuki Kawamata: "2-D Doubly-Indexed Block LMS Adaptive Filters"IEICE Society Conference on Fundamentals. A--4-10. 59 (1998)

Maha Shadaydeh、Masayuki Kawamata：“二维双索引块 LMS 自适应滤波器”IEICE 协会基础知识会议。