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Using computer algebra to perform image compression with wavelet transform and SVD

机译:使用计算机代数通过小波变换和SVD进行图像压缩

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Computer Algebra Software, especially Maple and its Image Tools package, is used to develop image compression using the Weibull distribution, Wavelet transform application and Singular Value Decomposition (SVD). For prototyping of the image compression process, Maple packages, Linear Algebra, Array Tools and Discrete Transform are used simultaneously with Image Tools image processing package. The image compression process implies the realization of matrix computing with high dimension matrices, and Maple software develops those operations easily and efficiently. Some image compression experiments are done, and the matrix dimension for minimum information needed to store an image is shown clearly, also the matrix dimension of redundant information. Implementation of algorithms for image compression in other computer algebra systems such as Mathematica and Maxima is proposed as future investigation path. Also it is proposed the use of curvelet transform as a tool for image compression.
机译:计算机代数软件,特别是Maple及其图像工具包,用于使用Weibull分布,小波变换应用程序和奇异值分解(SVD)开发图像压缩。对于图像压缩过程的原型,将Maple软件包,线性代数,阵列工具和离散变换与Image Tools图像处理软件包同时使用。图像压缩过程意味着使用高维矩阵实现矩阵计算,而Maple软件则可以轻松高效地开发这些操作。进行了一些图像压缩实验,清楚地显示了存储图像所需的最少信息的矩阵维,以及冗余信息的矩阵维。提出了在其他计算机代数系统(例如Mathematica和Maxima)中实现图像压缩算法的算法,作为未来的研究途径。还建议使用曲波变换作为图像压缩的工具。

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