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Visibility of wavelet quantization noise

机译:小波量化噪声的可见性

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The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression, measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r2/sup -/spl lambda//, where r is the display visual resolution in pixels/degree, and /spl lambda/ is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.
机译:离散小波变换(DWT)将图像分解为在空间频率和方向上变化的波段。它广泛用于图像压缩,需要对DWT量化误差的可见度进行测量才能实现最佳压缩。单个系数带的均匀量化会导致伪像,我们称之为DWT均匀量化噪声。它是相应DWT合成滤波器的随机幅度基函数的晶格的总和。我们测量了Y,Cb和Cr颜色通道中DWT均匀量化噪声样本的视觉检测阈值。小波的空间频率是r2 / sup-/ spl lambda //,其中r是显示视觉分辨率(以像素/度为单位),/ spl lambda /是小波级别。阈值随着小波空间频率的增加而迅速增加。阈值也从Y到Cr到Cb增大,并且方向从低通到水平/垂直到对角线。我们为DWT噪声检测阈值构建了一个数学模型,该模型是水平,方向和显示视觉分辨率的函数。这允许计算“在感知上无损”的量化矩阵,其所有误差理论上都在视觉阈值以下。该模型也可以用作自适应量化方案的基础。

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