Abstract: A method of dynamically adjusting power consumption for a computer system. The method includes the steps of setting a parameter table in the computer system and checking the computer system to obtain a parameter. The parameter is compared with the parameter table to obtain a result. According to the result and the parameter table, the clock throttling ratio of a CPU in the computer system is adjusted.

Abstract: The coded block parameters used to code blocks of image samples into structures called macroblocks are compressed more efficiently by exploiting the correlation between chrominance and luminance blocks in each macroblock. In particular, the coded block pattern for chrominance and luminance are combined into a single parameter for the macroblock and jointly coded with a single variable length code. To further enhance coding efficiency, the spatial coherence of coded block patterns can be exploited by using spatial prediction to compute predicted values for coded block pattern parameters.

Abstract: Techniques and tools for motion estimation and compensation are described. For example, a video encoder adaptively switches between different motion resolutions, which allows the encoder to select a suitable resolution for a particular video source or coding circumstances.

Abstract: Techniques and tools for processing reference frames in a motion estimation/compensation loop or motion compensation loop are described. For example, a video encoder or decoder filters reference frames to reduce discontinuities at block boundaries, improving the efficiency of motion estimation and compensation.

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 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: 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: Quantization matrices facilitate digital audio encoding and decoding. An audio encoder generates and compresses quantization matrices; an audio decoder decompresses and applies the quantization matrices. The invention includes several techniques and tools, which can be used in combination or separately. For example, the audio encoder can generate quantization matrices from critical band patterns for blocks of audio data. The encoder can compute the quantization matrices directly from the critical band patterns, which can be computed from the same audio data that is being compressed. The audio encoder/decoder can use different modes for generating/applying quantization matrices depending on the coding channel mode of multi-channel audio data. The audio encoder/decoder can use different compression/decompression modes for the quantization matrices, including a parametric compression/decompression mode.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: The coded block parameters used to code blocks of image samples into structures called macroblocks are compressed more efficiently by exploiting the correlation between chrominance and luminance blocks in each macroblock. In particular, the coded block pattern for chrominance and luminance are combined into a single parameter for the macroblock and jointly coded with a single variable length code. To further enhance coding efficiency, the spatial coherence of coded block patterns can be exploited by using spatial prediction to compute predicted values for coded block pattern parameters.

Abstract: An improved loss recovery method for coding streaming media classifies each data unit in the media stream as an independent data unit (I unit), a remotely predicted unit (R unit) or a predicted data unit (P unit). Each of these units is organized into independent segments having an I unit, multiple P units and R units interspersed among the P units. The beginning of each segment is the start of a random access point, while each R unit provides a loss recovery point that can be placed independently of the I unit. This approach separates the random access point from the loss recovery points provided by the R units, and makes the stream more impervious to data losses without substantially impacting coding efficiency. The most important data units are transmitted with the most reliability to ensure that the majority of the data received by the client is usable. The I units are the least sensitive to transmission losses because they are coded using only their own data.

Abstract: A transcoder reduces excess requantization error in quantization of spectral data. The transcoder phase shifts data decompressed by a decompressor. The phase shifting causes a change to corresponding spectral data produced in later transform coding of the decompressed data. When the spectral data is then quantized to reduce bitrate, the earlier phase shifting reduces excess requantization error. After transcoding, a second decompressor can compensate for the phase shifting by, for example, reverse shifting by the amount of the phase shift. Instead of phase shifting, the transcoder can reduce excess requantization error by, for example, adding random noise to the decompressed data or changing transform block sizes.

Abstract: An improved loss recovery method for coding streaming media classifies each data unit in the media stream as an independent data unit (I unit), a remotely predicted unit (R unit) or a predicted data unit (P unit). Each of these units is organized into independent segments having an I unit, multiple P units and R units interspersed among the P units. The beginning of each segment is the start of a random access point, while each R unit provides a loss recovery point that can be placed independently of the I unit. This approach separates the random access point from the loss recovery points provided by the R units, and makes the stream more impervious to data losses without substantially impacting coding efficiency. The most important data units are transmitted with the most reliability to ensure that the majority of the data received by the client is usable. The I units are the least sensitive to transmission losses because they are coded using only their own data.

Abstract: An encoder dynamically filters information for lossy compression so as to control bitrate or quality with few sudden, dramatic changes to perceptual quality of the compressed information. For example, a video encoder regulates the level of a buffer (e.g., how full or empty the buffer is) by adjusting median filtering of video information (e.g., pixel data and/or prediction residuals). The buffer stores compressed video information for the video encoder. Based upon the buffer level, the video encoder changes the median filter kernel applied to video information. If the buffer starts to get too full, the video encoder increases the size of the kernel, which tends to smooth the video information, introduce slight blurriness, and deplete the buffer. If the buffer starts to get too empty, the video encoder decreases the size of the kernel or stops filtering, which tends to preserve the video information and fill the buffer.

Abstract: The coded block parameters used to code blocks of image samples into structures called macroblocks are compressed more efficiently by exploiting the correlation between chrominance and luminance blocks in each macroblock. In particular, the coded block pattern for chrominance and luminance are combined into a single parameter for the macroblock and jointly coded with a single variable length code. To further enhance coding efficiency, the spatial coherence of coded block patterns can be exploited by using spatial prediction to compute predicted values for coded block pattern parameters.

Abstract: A motion estimation process improves coding efficiency by using a modified search criteria. The modified search criteria takes into account the error signal needed to encode a block of pixels as well as the the motion data when selecting a matching block in a target frame. This approach reduces the combined overhead of both the motion and error signal data for the encoded block of pixels. When used in conjunction with a spiral search path in the target frame, the modified search criteria improves the speed of the search because it eliminates the need for an exhaustive search. A predicted motion vector is used to optimize the search location. Preferably the search order is selected so that target pixels closer to predicted point are searched before pixels farther away in the target frame.

Abstract: A method of constructing a code book for groupings of symbols drawn from an alphabet, in which variable-sized groups of symbols are each assigned a variable length code based on probability of occurrence of symbol groupings. Code book entries are added by tentatively extending the high probability groupings with symbols from the alphabet. Code book size is restrained by identification of identify high probability symbol groupings, such that low probability groupings are combined into a single code book entry. Probability of occurrence for each entry is tracked. Extension and combination is repeated until a code book of predetermined size is reached. Each code book entry is assigned an entropy-type code according to the probability associated with each book entry.

Abstract: A semantic video object extraction system using mathematical morphology and perspective motion modeling. A user indicates a rough outline around an image feature of interest for a first frame in a video sequence. Without further user assistance, the rough outline is processed by a morphological segmentation tool to snap the rough outline into a precise boundary surrounding the image feature. Motion modeling is performed on the image feature to track its movement into a subsequent video frame. The motion model is applied to the precise boundary to warp the precise outline into a new rough outline for the image feature in the subsequent video frame. This new rough outline is then snapped to locate a new precise boundary. Automatic processing is repeated for subsequent video frames.

Abstract: Entropy encoding and decoding of data with a code book containing variable length entropy-type codes that are assigned to variable length input symbol groupings. The variable length input sequences are identified by scanning an input channel, such as a live broadcast, non-volatile data storage, or network connection (e.g., LAN, WAN, Internet). Each time a symbol grouping is recognized, a corresponding entropy-type code is output as a replacement for the input stream. Decoding is the inverse process of encoding, where a code word is looked up in the code book and the corresponding original input is obtained.

Abstract: A semantic video object extraction system using mathematical morphology and perspective motion modeling. A user indicates a rough outline around an image feature of interest for a first frame in a video sequence. Without further user assistance, the rough outline is processed by a morphological segmentation tool to snap the rough outline into a precise boundary surrounding the image feature. Motion modeling is performed on the image feature to track its movement into a subsequent video frame. The motion model is applied to the precise boundary to warp the precise outline into a new rough outline for the image feature in the subsequent video frame. This new rough outline is then snapped to locate a new precise boundary. Automatic processing is repeated for subsequent video frames.