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    • 2. 发明申请
    • COMPUTATIONAL MUSIC-TEMPO ESTIMATION
    • 计算音乐 - 速度估计
    • WO2008033433A2
    • 2008-03-20
    • PCT/US2007/019876
    • 2007-09-11
    • HEWLETT-PACKARD DEVELOPMENT COMPANY L.P.CHANG, Yu-YaoSAMADANI, RaminZHANG, TongWIDDOWSON, Simon
    • CHANG, Yu-YaoSAMADANI, RaminZHANG, TongWIDDOWSON, Simon
    • 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音乐剧选择的节奏的计算估计。 在下面描述的本发明的某些实施例中,分析音乐选择的一小部分以确定音乐选择的节奏。 对数字编码的音乐选择样本进行计算变换以产生对应于样本的功率谱,其又被变换以产生二维起始强度矩阵(618)。 然后将二维起始强度矩阵变换(806)为对应的一组频带(704-707)中的每一个的一组起始强度/时间函数(716)。 然后分析发作强度/时间函数以找到转换成由分析返回的估计节奏的最可靠的发作间隔(808,8100)(812)。
    • 8. 发明申请
    • REDUCING ARTIFACTS IN COMPRESSED IMAGES
    • 减少压缩图像中的人物
    • WO2005039187A1
    • 2005-04-28
    • PCT/US2004/032483
    • 2004-09-29
    • HEWLETT-PACKARD DEVELOPMENT COMPANY L.P.SAMADANI, RaminSUNDARARJAN, ArvindSAID, Amir
    • SAMADANI, RaminSUNDARARJAN, ArvindSAID, Amir
    • H04N7/26
    • H04N19/86H04N19/122H04N19/60
    • Systems and methods of reducing artifices in compressed images (12) are described. In one aspect, spatially-shifted forward transforms of the input image (12) are computed to generate respective sets of forward transform coefficients (C 1 , C 2 , …, C K ). Nonlinear transforms (T 1 , T 2 , …, T K ) are applied to the forward transform coefficients of each set (C 1 , C 2 , …, C K ). Inverse transforms (C’ 1 , C’ 2 , …, C’ K )of the sets of nonlinearly transformed forward transform coefficients are computed to generate respective intermediate images (I 1 , I 2 , …, I K ). Respective measures of local spatial intensity variability are computed for pixels of each of the intermediate images (I 1 , I 2 , …, I K ). An output image (40) is computed with pixel values computed based at least in part of the competed measures of the local spatial intensity variability.
    • 描述了在压缩图像(12)中减少工件的系统和方法。 在一个方面,计算输入图像(12)的空间位移正向变换,以产生各组正向变换系数(C1,C2,...,CK)。 非线性变换(T1,T2,...,TK)被应用于每个集合(C1,C2,...,CK)的正向变换系数。 计算非线性变换前向变换系数集合的逆变换(C'1,C'2,...,C'K)以生成各自的中间图像(I1,I2,...,IK)。 对于每个中间图像(I1,I2,...,IK)的像素,计算局部空间强度变异性的各个度量。 使用根据局部空间强度变异性的竞争测量的至少一部分计算的像素值计算输出图像(40)。
    • 10. 发明申请
    • TRANSFORMATIONS FOR DENOISING IMAGES
    • 用于隐形图像的变换
    • WO2005045760A2
    • 2005-05-19
    • PCT/US2004/035031
    • 2004-10-21
    • HEWLETT-PACKARD DEVELOPMENT COMPANY L.P.SAMADANI, Ramin
    • SAMADANI, Ramin
    • G06T5/10
    • G06T5/002G06T2207/10024H04N19/48H04N19/60H04N19/80H04N19/86
    • Systems and methods of denoising images (12) are described. In one aspect, spatially-shifted forward transforms (C 1 , C 2 , …, C k ) of an input image (62) are computed. Each forward transform (C 1 , C 2 , …, C k ) 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 Λ, 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 (C 1 , C 2 , …, C k ) 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 ).
    • 描述去噪图像(12)的系统和方法。 在一个方面,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'的去噪变换Z来计算每个正向变换(C1,C2,...,Ck),其中Z和Z'之间的矩阵乘法产生对角矩阵Lambda,Z = F(D) F指定从D的系数到Z的系数的映射,D基本对应于频域变换。 基于从与输入图像(62)链接的量化值导出的非线性映射,对正向变换(C1,C2,...,Ck)进行去噪。 计算去噪前向变换的空间位移逆变换(C'1,C'2,...,C'k)。 基于Z和Z'计算每个逆变换(C'1,C'2,...,C'k)。 基于空间变换逆变换(C'1,C'2,...,C'k)的组合来计算输出图像(40)。