Abstract: An audio encoder and decoder use architectures and techniques that improve the efficiency of quantization (e.g., weighting) and inverse quantization (e.g., inverse weighting) in audio coding and decoding. The described strategies include various techniques and tools, which can be used in combination or independently. For example, an audio encoder quantizes audio data in multiple channels, applying multiple channel-specific quantizer step modifiers, which give the encoder more control over balancing reconstruction quality between channels. The encoder also applies multiple quantization matrices and varies the resolution of the quantization matrices, which allows the encoder to use more resolution if overall quality is good and use less resolution if overall quality is poor. Finally, the encoder compresses one or more quantization matrices using temporal prediction to reduce the bitrate associated with the quantization matrices. An audio decoder performs corresponding inverse processing and decoding.

Abstract: An audio encoder and decoder use architectures and techniques that improve the efficiency of quantization (e.g., weighting) and inverse quantization (e.g., inverse weighting) in audio coding and decoding. The described strategies include various techniques and tools, which can be used in combination or independently. For example, an audio encoder quantizes audio data in multiple channels, applying multiple channel-specific quantizer step modifiers, which give the encoder more control over balancing reconstruction quality between channels. The encoder also applies multiple quantization matrices and varies the resolution of the quantization matrices, which allows the encoder to use more resolution if overall quality is good and use less resolution if overall quality is poor. Finally, the encoder compresses one or more quantization matrices using temporal prediction to reduce the bitrate associated with the quantization matrices. An audio decoder performs corresponding inverse processing and decoding.

Abstract: Video decoding innovations for using local picture identifiers and computing co-located information are described. In one aspect, a decoder identifies reference pictures in a reference picture list of a temporal direct prediction mode macroblock that match reference pictures used by a co-located macroblock using local picture identifiers. In another aspect, a decoder determines whether reference pictures used by blocks are the same by comparing local picture identifiers during calculation of boundary strength. In yet another aspect, a decoder determines a picture type of a picture and based on the picture type selectively skips or simplifies computation of co-located information for use in reconstructing direct prediction mode macroblocks outside the picture.

Abstract: Adjustment of hardware acceleration level in a video decoder utilizing hardware acceleration is described. Errors are detected in a bitstream as it is decoded using different levels of error detection based on decoding characteristics. A statistical analysis is performed on the error values as they are detected. In one technique, if the bitstream is categorized as fitting a high error rate state in a bitstream model, then hardware acceleration is dropped. In another technique, error statistics based on run-lengths of good and bad bitstream units are kept, and compared to predetermined thresholds. If the thresholds are exceeded, the hardware acceleration level is dropped. The level is dropped in order to take advantage of superior error handing abilities of software-based decoding over hardware-accelerated decoding.

Abstract: Techniques and tools for reordering of spectral coefficients in encoding and decoding are described herein. For certain types and patterns of content, coefficient reordering reduces redundancy that is due to periodic patterns in the spectral coefficients, making subsequent entropy encoding more efficient. For example, an audio encoder receives spectral coefficients logically organized along one dimension such as frequency, reorders at least some of the spectral coefficients, and entropy encodes the spectral coefficients after the reordering. Or, an audio decoder receives entropy encoded information for such spectral coefficients, entropy decodes the information, and reverses reordering of at least some of the spectral coefficients.

Abstract: Techniques and tools for prediction of spectral coefficients in encoding and decoding are described herein. For certain types and patterns of content, coefficient prediction exploits correlation between adjacent spectral coefficients, making subsequent entropy encoding more efficient. For example, an audio encoder predictively codes quantized spectral coefficients in the quantized domain and entropy encodes results of the predictive coding. Or, for a particular quantized spectral coefficient, an audio decoder entropy decodes a difference value, computes a predictor in the quantized domain, and combines the predictor and the difference value.

Abstract: A compressed digital audio signal is transmitted from an audio source along a connection wire to an audio receiver. The digital audio signal can encode digital audio data having different sampling frequencies, frames sizes, and other information. The audio receiver that receives the digital audio signal can decode and convert the compressed digital audio signal into multiple synchronized analog signals, which are used to drive multiple speakers. The audio receiver may also synchronize the audio data with associated video data so that the audio playback and video playback are “in sync”, despite delay introduced by the audio signal decoding at the audio receiver.

Abstract: An encoder uses multi-pass VBR control strategies to provide constant or relatively constant quality for VBR output while guaranteeing (within tolerance) either compressed file size or, equivalently, overall average bitrate. The control strategies include various techniques and tools, which can be used in combination or independently. For example, in a first pass, an audio encoder encodes a sequence of audio data partitioned into variable-size chunks. In a second pass, the encoder encodes the sequence according to control parameters to produce output of relatively constant quality. The encoder sets checkpoints in the second pass to adjust the control parameters and/or subsequent checkpoints. The encoder selectively considers a peak bitrate constraint to limit peak bitrate. The encoder stores auxiliary information from the first pass for use in the second pass, which increases the speed of the second pass. Finally, the encoder compares signatures for the input data to check consistency between passes.

Abstract: An audio encoder implements multi-channel coding decision, band truncation, multi-channel rematrixing, and header reduction techniques to improve quality and coding efficiency. In the multi-channel coding decision technique, the audio encoder dynamically selects between joint and independent coding of a multi-channel audio signal via an open-loop decision based upon (a) energy separation between the coding channels, and (b) the disparity between excitation patterns of the separate input channels. In the band truncation technique, the audio encoder performs open-loop band truncation at a cut-off frequency based on a target perceptual quality measure. In multi-channel rematrixing technique, the audio encoder suppresses certain coefficients of a difference channel by scaling according to a scale factor, which is based on current average levels of perceptual quality, current rate control buffer fullness, coding mode, and the amount of channel separation in the source.

Abstract: Error detecting and protection innovations for video decoders are described. For example, in a multithreaded video decoder, a picture extent discovery (PED) task detects an error in a video bitstream which corrupts a picture. The PED task then determines any PED sub-stage which have been completed for the picture, and based on this determination, performs error-handing PED operations. In another example, an entropy decoding (ED) task checks validity on a macroblock-by-macroblock basis using a redundant buffer to avoid overflows. Additionally, error recovery innovations are described which facilitate playback of a video bit stream at an arbitrary position. For example, a video decoder chooses a picture in the bit stream after the arbitrary position at which to begin decoding based on a determination of acceptable recovery time and/or acceptable picture quality.

Abstract: Error concealment techniques for video decoding are described. For example, a video decoder after finding a corrupted picture in a bit stream, finds a suitable neighbor for the corrupted picture. For example, the video decoder favors pictures with the same parity as the corrupted picture and considers picture order count and picture corruption in choosing a neighbor. The decoder then modifies syntax elements for the encoded video in the bit stream to allow the neighbor to be used in concealing the corruption in the corrupted picture. The modification of syntax elements can depend on the particular video decoder implementation. For example, in a software-only multithreaded video decoder, a task graph is modified, while in a system utilizing video acceleration, syntax elements for reference lists are modified.

Abstract: A decoder which can detect errors in MPEG-2 coefficient blocks can identify syntactically-correct blocks which have out-of-bounds coefficients. The decoder computes coefficient bounds based on quantization scalers and quantization matrices and compares these to coefficient blocks during decoding; if a block has out-of-bounds coefficients, concealment is performed on the block. In a decoder implemented all in software, coefficient bounds checking is performed on iDCT coefficients against upper and lower bounds in a spatial domain. In a decoder which performs iDCT in hardware, DCT coefficients are compared to an upper energy bound.

Abstract: An audio processing tool measures the quality of reconstructed audio data. For example, an audio encoder measures the quality of a block of reconstructed frequency coefficient data in a quantization loop. The invention includes several techniques and tools, which can be used in combination or separately. First, before measuring quality, the tool normalizes the block to account for variation in block sizes. Second, for the quality measurement, the tool processes the reconstructed data by critical bands, which can differ from the quantization bands used to compress the data. Third, the tool accounts for the masking effect of the reconstructed data, not just the masking effect of the original data. Fourth, the tool band weights the quality measurement, which can be used to account for noise substitution or band truncation. Finally, the tool changes quality measurement techniques depending on the channel coding mode.

Abstract: An audio processing tool measures the quality of reconstructed audio data. For example, an audio encoder measures the quality of a block of reconstructed frequency coefficient data in a quantization loop. The invention includes several techniques and tools, which can be used in combination or separately. First, before measuring quality, the tool normalizes the block to account for variation in block sizes. Second, for the quality measurement, the tool processes the reconstructed data by critical bands, which can differ from the quantization bands used to compress the data. Third, the tool accounts for the masking effect of the reconstructed data, not just the masking effect of the original data. Fourth, the tool band weights the quality measurement, which can be used to account for noise substitution or band truncation. Finally, the tool changes quality measurement techniques depending on the channel coding mode.

Abstract: Techniques and tools for representing, coding, and decoding scale factor information are described herein. For example, during encoding of scale factors, an encoder uses one or more of flexible scale factor resolution selection, spatial prediction of scale factors, flexible prediction of scale factors, smoothing of noisy scale factor amplitudes, reordering of scale factor prediction residuals, and prediction of scale factor prediction residuals. Or, during decoding, a decoder uses one or more of flexible scale factor resolution selection, spatial prediction of scale factors, flexible prediction of scale factors, reordering of scale factor prediction residuals, and prediction of scale factor prediction residuals.

Abstract: Reference pictures can be created to assist with video decoding. For example, a method for decoding video can comprise receiving an encoded video bit stream, determining that a reference picture is needed, and creating and inserting the reference picture into the encoded video bit stream. A method for decoding video can also comprise receiving an encoded video bit stream, performing bit stream parsing, determining that a reference picture is needed, selecting a representation level for the reference picture, and conveying data for the selected reference picture to a hardware accelerated graphics processing unit. Various video operations, such as creating reference pictures and related information, can be performed by central processing units, while other video decoding operations can be performed by graphics processing units.

Abstract: An audio encoder and decoder use architectures and techniques that improve the efficiency of multi-channel audio coding and decoding. The described strategies include various techniques and tools, which can be used in combination or independently. For example, an audio encoder performs a pre-processing multi-channel transform on multi-channel audio data, varying the transform so as to control quality. The encoder groups multiple windows from different channels into one or more tiles and outputs tile configuration information, which allows the encoder to isolate transients that appear in a particular channel with small windows, but use large windows in other channels. Using a variety of techniques, the encoder performs flexible multi-channel transforms that effectively take advantage of inter-channel correlation. An audio decoder performs corresponding processing and decoding. In addition, the decoder performs a post-processing multi-channel transform for any of multiple different purposes.

Abstract: A transform coder adaptively configures window sizes for transform coding in a two-pass process to maximize coding efficiency, while achieving necessary time resolution to avoid pre-echo. In a first pass, the coder places small size windows over detected transient regions of an input signal in an open-loop window configuration process. In a second pass, the coder adjusts the window size configuration according to measurements of the achieved quality in a closed-loop window configuration process. Where quality measurement shows unacceptable quantization noise, the coder increases window size. Where pre-echo is detected, the coder reduces window size within coding bit rate constraints.

Abstract: An audio encoder and decoder use architectures and techniques that improve the efficiency of multi-channel audio coding and decoding. The described strategies include various techniques and tools, which can be used in combination or independently. For example, an audio encoder performs a pre-processing multi-channel transform on multi-channel audio data, varying the transform so as to control quality. The encoder groups multiple windows from different channels into one or more tiles and outputs tile configuration information, which allows the encoder to isolate transients that appear in a particular channel with small windows, but use large windows in other channels. Using a variety of techniques, the encoder performs flexible multi-channel transforms that effectively take advantage of inter-channel correlation. An audio decoder performs corresponding processing and decoding. In addition, the decoder performs a post-processing multi-channel transform for any of multiple different purposes.

Abstract: CBR control strategies provide constant or relatively constant bitrate output with variable quality. The control strategies include various techniques and tools, which can be used in combination or independently. For example, an audio encoder uses a trellis in two-pass or delayed-decision CBR encoding. The trellis nodes are states derived by quantizing buffer fullness values. The transitions between nodes of a previous stage and nodes of a current stage depend on encoding a current chunk of audio at different quality levels. When pruning the trellis, the encoder uses a cost function that considers smoothness in quality as well as quality in absolute terms. The encoder may store compressed data at different quality levels, then output the compressed data after simplification of the trellis to a suitable point. If the two-pass or delayed-decision CBR encoding fails, the encoder uses one-pass CBR encoding for the sequence or part of the sequence.