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    • 2. 发明申请
    • COMPUTATIONAL MUSIC-TEMPO ESTIMATION
    • 计算音乐温度估计
    • WO2008033433A3
    • 2008-09-25
    • PCT/US2007019876
    • 2007-09-11
    • HEWLETT PACKARD DEVELOPMENT COCHANG YU-YAOSAMADANI RAMINZHANG TONGWIDDOWSON SIMON
    • CHANG YU-YAOSAMADANI RAMINZHANG TONGWIDDOWSON SIMON
    • G10H1/40
    • G10H1/40G10H2210/076
    • Various method and system embodiments of the present invention are directed to computational estimation of a tempo for a digitally encoded musical selection. In certain embodiments of the present invention, described below, a short portion of a musical selection is analyzed to determine the tempo of the musical selection. The digitally encoded musical selection sample is computationally transformed to produce a power spectrum corresponding to the sample, in turn transformed to produce a two-dimensional strength-of-onset matrix (618). The two-dimensional strength-of-onset matrix is then transformed (806) into a set of strength-of-onset/time functions (716) for each of a corresponding set of frequency bands (704-707). The strength-of-onset/time functions are then analyzed to find a most reliable onset interval (808, 8100) that is transformed into an estimated tempo returned by the analysis (812).
    • 本发明的各种方法和系统实施例涉及用于数字编码的音乐选择的速度的计算估计。 在下面描述的本发明的某些实施例中,分析音乐选择的短部分以确定音乐选择的速度。 对数字编码的音乐选择样本进行计算转换,以产生对应于样本的功率谱,然后被转换以产生二维强度起始矩阵(618)。 然后,对于相应的一组频带(704-707)中的每一个,将二维强度发射矩阵转换(806)成一组起始/时间功能强度(716)。 然后分析发作强度/时间函数以找到被转换成由分析返回的估计节奏的最可靠的发起间隔(808,8100)(812)。
    • 7. 发明申请
    • TRANSFORMATIONS FOR DENOISING IMAGES
    • 消除图像的转换
    • WO2005045760A3
    • 2005-11-10
    • PCT/US2004035031
    • 2004-10-21
    • HEWLETT PACKARD DEVELOPMENT COSAMADANI RAMIN
    • SAMADANI RAMIN
    • G06T5/00G06T5/10G06T9/00H04N7/26H04N7/30
    • G06T5/002G06T2207/10024H04N19/48H04N19/60H04N19/80H04N19/86
    • Systems and methods of denoising images (12) are described. In one aspect, spatially-shifted forward transforms (C1, C2, ..., Ck) of an input image (62) are computed. Each forward transform (C1, C2, ..., Ck) is computed based on a denoiser transform Z having an associated transpose Z', wherein a matrix multiplication between Z and Z'produces a diagonal matrix Lambda, Z = F(D), F specifies a mapping from coefficients of D to coefficients of Z, and D substantially corresponds to a frequency-domain transform. The forward transforms (C1, C2, ..., Ck) are denoised based on nonlinear mappings derived from quantization values linked to the input image (62). Spatially-shifted inverse transforms (C'1, C'2, ..., C'k) of the denoised forward transforms are computed. Each inverse transform (C'1, C'2, ..., C'k) is computed based on Z and Z'. An output image (40) is computed based on a combination of spatially-shifted inverse transforms (C'1, C'2, ..., C'k).
    • 描述了对图像进行去噪的系统和方法(12)。 在一个方面中,计算输入图像(62)的空间位移正向变换(C1,C2,...,Ck)。 基于具有相关联的转置Z'的降噪器变换Z来计算每个正向变换(C1,C2,...,Ck),其中Z和Z'之间的矩阵相乘产生对角矩阵Lambda,Z = F(D) F指定从D的系数到Z的系数的映射,并且D基本上对应于频域变换。 基于从链接到输入图像(62)的量化值导出的非线性映射对正向变换(C1,C2,...,Ck)进行去噪。 计算经去噪的正向变换的空间移位逆变换(C'1,C'2,...,C'k)。 基于Z和Z'计算每个逆变换(C'1,C'2,...,C'k)。 基于空间位移反变换(C'1,C'2,...,C'k)的组合来计算输出图像(40)。