摘要:
A method for optimization of rate-distortion for Advanced Audio Coding (AAC). The method provides for the identification of quantized spectral coefficient sequences for optimization of rate-distortion. The method also provides joint optimization of scale factors, Huffman codebooks and quantized spectral coefficient sequences for minimization of a rate-distortion cost. The method provides an iterative rate-distortion optimization algorithm for AAC encoding. In each iteration, the method first finds the optimal scale factors and quantized spectral coefficients when Huffman codebooks are fixed, then updates Huffman codebooks and quantized spectral coefficients given the optimized scale factors. The iterations may be applied until a predetermined threshold is attained.
摘要:
An iterative rate-distortion optimization algorithm for MPEG I/II Layer-3 (MP3) encoding based on the method of Lagrangian multipliers. Generally, an iterative method is performed such that a global quantization step size is determined while scale factors are fixed, and thereafter the scale factors are determined while the global quantization step size is fixed. This is repeated until a calculated rate-distortion cost is within a predetermined threshold. The methods are demonstrated to be computationally efficient and the resulting bit stream is fully standard compatible.
摘要翻译:基于拉格朗日乘数法的MPEG I / II Layer-3(MP3)编码的迭代速率失真优化算法。 通常,执行迭代方法,使得在比例因子固定的同时确定全局量化步长,此后在全局量化步长固定的同时确定比例因子。 直到计算出的速率 - 失真成本在预定的阈值内为止。 这些方法被证明在计算上是有效的,并且所得到的比特流是完全标准兼容的。
摘要:
An iterative rate-distortion optimization algorithm for MPEG I/II Layer-3 (MP3) encoding based on the method of Lagrangian multipliers. Generally, an iterative method is performed such that a global quantization step size is determined while scale factors are fixed, and thereafter the scale factors are determined while the global quantization step size is fixed. This is repeated until a calculated rate-distortion cost is within a predetermined threshold. The methods are demonstrated to be computationally efficient and the resulting bit stream is fully standard compatible.
摘要翻译:基于拉格朗日乘数法的MPEG I / II Layer-3(MP3)编码的迭代速率失真优化算法。 通常,执行迭代方法,使得在比例因子固定的同时确定全局量化步长,此后在全局量化步长固定的同时确定比例因子。 直到计算出的速率 - 失真成本在预定的阈值内为止。 这些方法被证明在计算上是有效的,并且所得到的比特流是完全标准兼容的。
摘要:
An iterative rate-distortion optimization algorithm for MPEG I/II Layer-3 (MP3) encoding based on the method of Lagrangian multipliers. Generally, an iterative method is performed such that a global quantization step size is determined while scale factors are fixed, and thereafter the scale factors are determined while the global quantization step size is fixed. This is repeated until a calculated rate-distortion cost is within a predetermined threshold. The methods are demonstrated to be computationally efficient and the resulting bit stream is fully standard compatible.
摘要翻译:基于拉格朗日乘数法的MPEG I / II Layer-3(MP3)编码的迭代速率失真优化算法。 通常,执行迭代方法,使得在比例因子固定的同时确定全局量化步长,此后在全局量化步长固定的同时确定比例因子。 直到计算出的速率 - 失真成本在预定的阈值内为止。 这些方法被证明在计算上是有效的,并且所得到的比特流是完全标准兼容的。
摘要:
A method, system and computer program product are provided for progressively encoding a digitized color image using a data processing system, the digitized color image being provided by assigning each of the M distinct colors to at least one pixel in the set of pixels. This involves initializing and growing the tree structure by selecting a leaf node n to become a non-leaf node n linked to two new leaf nodes based on an associated achievable cost, wherein the associated achievable cost is based on 1) a determined associated change in distortion resulting from turning the leaf node into the non-leaf node linked to the two new leaf nodes; and 2) a determined associated increase in entropy rate resulting from turning the leaf node into the non-leaf node linked to the two new leaf nodes.
摘要:
A method, system and computer program product for progressively encoding a digitized color image is provided. This involves: initializing a tree structure with at least one starting leaf node; determining at least one representative color for each starting leaf node; and growing the tree structure by (i) selecting a leaf node n to become a non-leaf node n linked to two new leaf nodes based on an associated achievable cost; (ii) creating the two new leaf nodes by re-allocating each color in n; (iii) determining a representative color for each of the two new leaf nodes; and (iv) encoding the index information associated with the leaf node n, the representative colors of the two new leaf nodes, and information regarding a plurality of pixels of the digitized color image corresponding to the two representative colors of the two new leaf nodes.
摘要:
A sequence of n coefficients is compressed by determining a cost-determined sequence of n coefficient indices represented by a cost-determined sequence of (run, index derivative) pairs under a given quantization table and run-index derivative coding distribution, wherein each sequence of (run, index derivative) pairs defines a corresponding sequence of coefficient indices such that (i) each index in the corresponding sequence of coefficient indices is a digital number, (ii) the corresponding sequence of coefficient indices includes a plurality of values including a special value, and (iii) each (run, index derivative) pair defines a run value representing a number of consecutive indices of the special value, and an index-based value derived from a value of the index following the number of consecutive indices of the special value. This involves (a) using the given quantization table and run-index derivative coding distribution to formulate a cost function for a plurality of possible sequences of (run, index derivative) pairs; (b) applying the cost function to each possible sequence in the plurality of possible sequences of (run, index derivative) pairs to determine an associated cost; and, (c) selecting the cost-determined sequence of (run, index derivative) pairs from the plurality of possible sequences of (run, index derivative) pairs based on the associated cost of each of the plurality of possible sequences of (run, index derivative) pairs; and encoding the corresponding selected cost-determined sequence of (run, index derivative) pairs using entropy coding based on a run-index derivative coding distribution.
摘要:
A sequence of n coefficients is compressed by determining a cost-determined sequence of n coefficient indices represented by a cost-determined sequence of (run, index derivative) pairs under a given quantization table and run-index derivative coding distribution, wherein each sequence of (run, index derivative) pairs defines a corresponding sequence of coefficient indices such that (i) each index in the corresponding sequence of coefficient indices is a digital number, (ii) the corresponding sequence of coefficient indices includes a plurality of values including a special value, and (iii) each (run, index derivative) pair defines a run value representing a number of consecutive indices of the special value, and an index-based value derived from a value of the index following the number of consecutive indices of the special value. This involves (a) using the given quantization table and run-index derivative coding distribution to formulate a cost function for a plurality of possible sequences of (run, index derivative) pairs; (b) applying the cost function to each possible sequence in the plurality of possible sequences of (run, index derivative) pairs to determine an associated cost; and, (c) selecting the cost-determined sequence of (run, index derivative) pairs from the plurality of possible sequences of (run, index derivative) pairs based on the associated cost of each of the plurality of possible sequences of (run, index derivative) pairs; and encoding the corresponding selected cost-determined sequence of (run, index derivative) pairs using entropy coding based on a run-index derivative coding distribution.
摘要:
A sequence of n coefficients is compressed by determining a cost-determined sequence of n coefficient indices represented by a cost-determined sequence of (run, index derivative) pairs under a given quantization table and run-index derivative coding distribution, wherein each sequence of (run, index derivative) pairs defines a corresponding sequence of coefficient indices such that (i) each index in the corresponding sequence of coefficient indices is a digital number, (ii) the corresponding sequence of coefficient indices includes a plurality of values including a special value, and (iii) each (run, index derivative) pair defines a run value representing a number of consecutive indices of the special value, and an index-based value derived from a value of the index following the number of consecutive indices of the special value. This involves (a) using the given quantization table and run-index derivative coding distribution to formulate a cost function for a plurality of possible sequences of (run, index derivative) pairs; (b) applying the cost function to each possible sequence in the plurality of possible sequences of (run, index derivative) pairs to determine an associated cost; and, (c) selecting the cost-determined sequence of (run, index derivative) pairs from the plurality of possible sequences of (run, index derivative) pairs based on the associated cost of each of the plurality of possible sequences of (run, index derivative) pairs; and encoding the corresponding selected cost-determined sequence of (run, index derivative) pairs using entropy coding based on a run-index derivative coding distribution.
摘要:
A sequence of n coefficients is compressed by determining a cost-determined sequence of n coefficient indices represented by a cost-determined sequence of (run, index derivative) pairs under a given quantization table and run-index derivative coding distribution, wherein each sequence of (run, index derivative) pairs defines a corresponding sequence of coefficient indices such that (i) each index in the corresponding sequence of coefficient indices is a digital number, (ii) the corresponding sequence of coefficient indices includes a plurality of values including a special value, and (iii) each (run, index derivative) pair defines a run value representing a number of consecutive indices of the special value, and an index-based value derived from a value of the index following the number of consecutive indices of the special value. This involves (a) using the given quantization table and run-index derivative coding distribution to formulate a cost function for a plurality of possible sequences of (run, index derivative) pairs; (b) applying the cost function to each possible sequence in the plurality of possible sequences of (run, index derivative) pairs to determine an associated cost; and, (c) selecting the cost-determined sequence of (run, index derivative) pairs from the plurality of possible sequences of (run, index derivative) pairs based on the associated cost of each of the plurality of possible sequences of (run, index derivative) pairs; and encoding the corresponding selected cost-determined sequence of (run, index derivative) pairs using entropy coding based on a run-index derivative coding distribution.