文件名称:wavelet-image
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二维图像信号的去噪步骤:
(1)二维图像信号的小波分解。选择合适的小波与恰当的分解层次N,并对待压缩的二维图像信号进行N层分解计算。
(2)对分解后的每一层高频系数,选择一个恰当的阈值,并对该层高频系数进行软阈值量化处理。
(3)二维图像信号的小波重构。用小波分解后的第N层近似(低频系数)和经过阈值量化处理后的各层细节(高频系数),对二维信号进行小波重构。-Two-dimensional image signal denoising steps: (1) two-dimensional image signal wavelet decomposition. Select the appropriate wavelet decomposition level and the appropriate N, and treatment of compressed N-layer two-dimensional image signal decomposition calculations. (2) of the decomposition of high-frequency coefficients of each layer, select an appropriate threshold, and high-frequency coefficients of the layer of soft threshold quantification. (3) Wavelet two-dimensional image reconstruction. Wavelet decomposition of the first N-layer approximation (low frequency factor) and through the quantification of threshold levels after the details (high frequency coefficients), two-dimensional wavelet reconstruction signal.
(1)二维图像信号的小波分解。选择合适的小波与恰当的分解层次N,并对待压缩的二维图像信号进行N层分解计算。
(2)对分解后的每一层高频系数,选择一个恰当的阈值,并对该层高频系数进行软阈值量化处理。
(3)二维图像信号的小波重构。用小波分解后的第N层近似(低频系数)和经过阈值量化处理后的各层细节(高频系数),对二维信号进行小波重构。-Two-dimensional image signal denoising steps: (1) two-dimensional image signal wavelet decomposition. Select the appropriate wavelet decomposition level and the appropriate N, and treatment of compressed N-layer two-dimensional image signal decomposition calculations. (2) of the decomposition of high-frequency coefficients of each layer, select an appropriate threshold, and high-frequency coefficients of the layer of soft threshold quantification. (3) Wavelet two-dimensional image reconstruction. Wavelet decomposition of the first N-layer approximation (low frequency factor) and through the quantification of threshold levels after the details (high frequency coefficients), two-dimensional wavelet reconstruction signal.
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小波图像消噪.doc
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