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Image and video processing using discrete fractional transforms - Springer

机译:使用离散分数变换的图像和视频处理-Springer

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The mathematical transforms such as Fourier transform, wavelet transform and fractional Fourier transform have long been influential mathematical tools in information processing. These transforms process signal from time to frequency domain or in joint time–frequency domain. In this paper, with the aim to review a concise and self-reliant course, the discrete fractional transforms have been comprehensively and systematically treated from the signal processing point of view. Beginning from the definitions of fractional transforms, discrete fractional Fourier transforms, discrete fractional Cosine transforms and discrete fractional Hartley transforms, the paper discusses their applications in image and video compression and encryption. The significant features of discrete fractional transforms benefit from their extra degree of freedom that is provided by fractional orders. Comparison of performance states that discrete fractional Fourier transform is superior in compression, while discrete fractional cosine transform is better in encryption of image and video. Mean square error and peak signal-to-noise ratio with optimum fractional order are considered quality check parameters in image and video.
机译:诸如傅立叶变换,小波变换和分数阶傅立叶变换之类的数学变换长期以来一直是信息处理中具有影响力的数学工具。这些将处理信号从时域转换到频域或在联合时频域中转换。在本文中,为了回顾一个简洁且自力更生的过程,从信号处理的角度对离散分数变换进行了全面而系统的处理。从分数变换,离散分数傅里叶变换,离散分数余弦变换和离散分数Hartley变换的定义开始,本文讨论了它们在图像和视频压缩与加密中的应用。离散分数变换的显着特征得益于分数阶提供的额外自由度。性能比较表明,离散分数阶傅里叶变换的压缩效果更好,而离散分数阶余弦变换的图像和视频加密效果更好。均方误差和具有最佳分数阶的峰值信噪比被认为是图像和视频中的质量检查参数。

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