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B-spline wavelets for signal denoising and image compression - Springer

机译:B样条小波用于信号去噪和图像压缩-Springer

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In this paper we propose to develop novel techniques for signal/image decomposition, and reconstruction based on the B-spline mathematical functions. Our proposed B-spline based multiscale/resolution representation is based upon a perfect reconstruction analysis/synthesis point of view. Our proposed B-spline analysis can be utilized for different signal/imaging applications such as compression, prediction, and denoising. We also present a straightforward computationally efficient approach for B-spline basis calculations that is based upon matrix multiplication and avoids any extra generated basis. Then we propose a novel technique for enhanced B-spline based compression for different image coders by preprocessing the image prior to the decomposition stage in any image coder. This would reduce the amount of data correlation and would allow for more compression, as will be shown with our correlation metric. Extensive simulations that have been carried on the well-known SPIHT image coder with and without the proposed correlation removal methodology are presented. Finally, we utilized our proposed B-spline basis for denoising and estimation applications. Illustrative results that demonstrate the efficiency of the proposed approaches are presented.
机译:在本文中,我们建议开发用于信号/图像分解和基于B样条数学函数的重构的新技术。我们提出的基于B样条的多尺度/分辨率表示方法基于完美的重构分析/综合观点。我们提出的B样条分析可用于不同的信号/成像应用,例如压缩,预测和去噪。我们还为B样条基计算提供了一种简单的计算有效方法,该方法基于矩阵乘法,并且避免了任何额外的生成基数。然后,我们提出了一种新技术,可通过在任何图像编码器的分解阶段之前对图像进行预处理来对不同的图像编码器进行基于增强B样条的压缩。如我们的相关度量所示,这将减少数据相关的数量并允许更多的压缩。介绍了在有或没有建议的相关性去除方法的情况下,在众所周知的SPIHT图像编码器上进行的大量仿真。最后,我们将我们提出的B样条基础用于去噪和估计应用。说明性结果证明了所提出方法的有效性。

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