245 results about "Adaptive compression" patented technology

An adaptive compression mechanism that dynamically selects compression algorithms applied to network application traffic to improve performance. One implementation includes an arbitration scheme that reduces the impact on computing resources required to analyze different compression algorithms for different network applications. The adaptive compression functionality of the present invention can be integrated into network application traffic management or acceleration systems.

An efficient method for compressing sampled analog signals in real time, without loss, or at a user-specified rate or distortion level, is described. The present invention is particularly effective for compressing and decompressing high-speed, bandlimited analog signals that are not appropriately or effectively compressed by prior art speech, audio, image, and video compression algorithms due to various limitations of such prior art compression solutions. The present invention's preprocessor apparatus measures one or more signal parameters and, under program control, appropriately modifies the preprocessor input signal to create one or more preprocessor output signals that are more effectively compressed by a follow-on compressor. In many instances, the follow-on compressor operates most effectively when its input signal is at baseband. The compressor creates a stream of compressed data tokens and compression control parameters that represent the original sampled input signal using fewer bits. The decompression subsystem uses a decompressor to decompress the stream of compressed data tokens and compression control parameters. After decompression, the decompressor output signal is processed by a post-processor, which reverses the operations of the preprocessor during compression, generating a postprocessed signal that exactly matches (during lossless compression) or approximates (during lossy compression) the original sampled input signal. Parallel processing implementations of both the compression and decompression subsystems are described that can operate at higher sampling rates when compared to the sampling rates of a single compression or decompression subsystem. In addition to providing the benefits of real-time compression and decompression to a new, general class of sampled data users who previously could not obtain benefits from compression, the present invention also enhances the performance of test and measurement equipment (oscilloscopes, signal generators, spectrum analyzers, logic analyzers, etc.), busses and networks carrying sampled data, and data converters (A / D and D / A converters).

An imaging system incorporating adaptive compression which includes determining linear predictive differential residuals from an imager array pixel row. The differential residuals are classified into categories, each category having a range of differential residuals associated with it. The categories are analyzed to produce an ordered list having categories with most to least frequent residuals falling within a respective residual range associated with a respective category. The ordered list is then used to select a variable length encoding table with a matching ordered list. Variable length encoded category and range position offset data is output to a serializer unit, where the range position offset refers to a position in a range associated with a particular category.

Methods and apparatus for performing adaptive compression are disclosed. A data stream is divided into a plurality of data segments. When one of the plurality of data segments is compressed, it is determined whether the compression has been successful. When the compression has been successful, a data segment in proximity to the compressed segment (e.g., the next data segment in the plurality of data segments) is compressed. However, when the compression has been unsuccessful, one or more of the plurality of data segments are skipped (i.e., not compressed) before compression is attempted on another one of the plurality of data segments. When a data segment is compressed, the compression algorithm (and any associated parameter(s)) that is applied is selected based upon a variety of factors, such as the length of the data segment, CPU speed, CPU availability, and / or data throughput such as the network bandwidth or network availability (e.g., where data is to be transmitted via a network interface). The compression algorithm (and any associated parameter(s)) may also be selected, at least in part, based upon a set of user preferences that indicate a preference between the speed with which compression is performed and the amount that a data segment is compressed.

An adaptive compression technique which is an improvement to Lempel-Ziv (LZ) compression techniques, both as applied for purposes of reducing required storage space and for reducing the transmission time associated with transferring data from point to point. Pre-filled compression dictionaries are utilized to address the problem with prior Lempel-Ziv techniques in which the compression software starts with an empty compression dictionary, whereby little compression is achieved until the dictionary has been filled with sequences common in the data being compressed. In accordance with the invention, the compression dictionary is pre-filled, prior to the beginning of the data compression, with letter sequences, words and / or phrases frequent in the domain from which the data being compressed is drawn. The letter sequences, words, and / or phrases used in the pre-filled compression dictionary may be determined by statistically sampling text data from the same genre of text. Multiple pre-filled dictionaries may be utilized by the compression software at the beginning of the compression process, where the most appropriate dictionary for maximum compression is identified and used to compress the current data. These modifications are made to any of the known Lempel-Ziv compression techniques based on the variants detailed in 1977 and 1978 articles by Ziv and Lempel.

An apparatus and method for encoding video frames is provided. The video frames are divided into blocks for encoding. Encoding of the video blocks utilizes motion detection, motion estimation and adaptive compression, to obtain the desired compression for a particular bit rate. Adaptive compression includes intra compression (without regard to other frames) and inter compression (with regard to other frames). Intra compression, inter compression with motion detection, and inter compression with motion estimation are performed on a block by block basis, as needed. Segmentation is provided to compare encoding of a block with encoding of its sub-blocks, and to select the best block size for encoding.

The invention discloses an adaptive compressed sensing-based non-local reconstruction method for a natural image. The problems of serious reconstructed image information loss and the like in the prior art are mainly solved. The method is implemented by the steps of: (1) dividing an image into N 32*32 sub-blocks, obtaining a basic sensing matrix Phi' according to a basic sampling rate b and a sensing matrix Phi, and sampling a signal by utilizing Phi' to obtain a basic observation vector; (2) estimating a standard deviation sequence {d1, d2, ..., and dN} of the image according to the basic observation vector; (3) adaptively allocating a sampling rate ai for each sub-block according to the standard deviation sequence {d1, d2, ..., and dN}, and constructing an adaptive sensing matrix, and sampling the signal by utilizing the adaptive sensing matrix to obtain an adaptive observation vector; (4) forming an observation vector of each sub-block by using the basic observation vector and the adaptive observation vector; (5) obtaining an initial solution x0 of the image according to the observation vector; and (6) performing iteration by using x0, and reconstructing the original image until consistency with a finishing condition is achieved to obtain a reconstructed image x'. The method has the advantages of high image reconstruction quality, clear principle and operational simplicity, and is applied to the sampling and reconstruction of the natural image.

Systems, devices and methods for providing active and / or passive compression therapy to a body part can include a compression device worn over a compression stocking. The compression device can have a pulley based drive train that is driven by a motor to tighten and loosen compression elements, such as compression straps, in a precise, rapid, and balanced manner. Sensors can be used in the compression device and / or compression stockings to provide feedback to modulate the compression treatment parameters.

From a raster page, patches of connected pixels of the same color are identified. Patches of at least a predetermined sized, typically corresponding to text or line art objects, are subjected to a lossless compression. Patches below the predetermined size, typically corresponding to image or photo objects, are substantially subjected to a lossy compression. The patch predetermined size controls the mix of lossless and lossy compression procedures. Optimum compression is achieved by maximizing the lossless compression while attaining a targeted compression ratio. Various features include efficient recognition and encoding of patches, refined treatment of the boundaries between the lossless- and the lossy-compressed pixels, adaptive compression ratio control, and fail-safe compression provisions.

The invention discloses a self-adaptation compression reconstruction method based on energy effectiveness observation in a cognitive sensor network. The self-adaptation compression reconstruction method based on the energy effectiveness observation in the cognitive sensor network comprises the steps that (1) a node carries out local detection and compression measurement on data which are actually sensed through an analog transcriber according to the characteristic that power consumption of the node of a cognitive sensor is limited, (2) a space-time relevance structure of sensing signals is used, sensing data are mapped to a wavelet orthogonal basis cascading dictionary to carry out sparse conversion and to carry out self-adaptation observation through a weighting energy subset function, appropriate observation values are obtained in an energy effectiveness mode, orthogonalization is carried out on selected observation vectors to construct a measurement matrix, (3) the sensing data after compression measurement are fed back to an aggregation node through a report channel, the aggregation node carries out self-adaptation reconstruction on the sensing data by using a gradient projection sparse reconstruction Barzilai-Borwein method based on a convex relaxation method, and effective compromise between reconstruction performance and energy consumption of the node is achieved. The self-adaptation compression reconstruction method based on the energy effectiveness observation in the cognitive sensor network can carry out accurate reconstruction on the sensing signals, ensures energy effectiveness of the sensing node, and has actual application significance.

A network device is adaptively configured to compress an output data stream, responsive to congestion in the network. The network device receives indications of network congestion from another network device. Upon receipt of a congestion indication, the network device can adapt the compression technique to attempt to achieve more or less compression, depending on whether the congestion indication indicates more or less congestion. By adapting the compression to the level of network congestion, end-to-end latency of the network can potentially be decreased.

A computer-implemented method for compressing a first stream of data, the first stream of data comprising a plurality of input words. The computer-implemented method includes receiving the plurality input words, and adaptively compressing the plurality of input words into a plurality of compression codes. The computer-implemented method further includes outputting the plurality of compression codes upon encountering an end-of-file signal in the first stream of data, wherein the plurality of compression codes are fewer in number than the number of unique bit patterns requiring unique compression codes under LZW (Lempel Ziv & Welch) compression.

An apparatus and method of compressing a structured document. The structured document is searched once for first and second marks, a first mark indicating a start of an element of the structured document, and a second mark indicating an end of an element of the structured document. When encountering a first mark in the searching step, a representation of the first mark is output and a level counter is incremented, a value of the level counter indicating on which level in the structured document an element is located. When encountering a second mark in the searching step, a second code data is output and the level counter is decremented.

A method, system, and apparatus are directed towards compression of content. A portion of content may be compressed using a compression mode. One or more criteria may be evaluated. Based on the evaluated criteria, a decision is made as to whether to select a different compression mode. If selected, the different compression mode may be used to compress another portion of the content. Additional compression modes may be selected and used to compress the content.

An apparatus and method for encoding video frames is provided. The video frames are divided into blocks for encoding. Encoding of the video blocks utilizes motion detection, motion estimation and adaptive compression, to obtain the desired compression for a particular bit rate. Adaptive compression includes intra compression (without regard to other frames) and inter compression (with regard to other frames). Intra compression, inter compression with motion detection, and inter compression with motion estimation are performed on a block by block basis, as needed. Segmentation is provided to compare encoding of a block with encoding of its sub-blocks, and to select the best block size for encoding.

The invention relates to an adaptive H.264 compressed domain video watermark embedding and extracting method in the technical field of information security, which can realize the real-time operation of video information hiding. The threshold value of a motion vector is adaptively adjusted according to watermark embedding amount statistical data of an adjacent frame, so that watermark capacity is ensured and the requirement of embedding a one-time watermark among a few frames is met; and error diffusion caused by modifying the motion vector is accurately positioned in a partial interframe prediction mode, so that good drift and distortion compensation effects can be achieved.

Additional computing power is captured using the idle processing power of mobile phones incorporated into a grid computing system, wherein the system is capable of pushing projects out to available mobile phones for processing during idle operation times. To further efficiently utilize the unused processing cycles of mobile phones, a unique protocol is utilized to coordinate processing tasks which makes use of existing short messages techniques to communicate projects. The unique protocol is combination of bootstrapping using standard compression techniques along with an adaptive compression scheme.

The invention discloses a multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method, which relates to the technical field of information and communication. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method is provided for solving the problem of recovering an original multiband signal from multiple observed value vectors with unknown sparsity after continuous-limited module conversion through sampling by a modulated broadband converter under an Xampling framework. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method comprises the steps of: conducting self-adaptive estimation on sparsity of a signal; updating the sparsity with a given step length factor through repeated iteration so that the sparsity gradually approaches the actual sparsity of the signal; correcting a support set through a backtracking thought and a minimum mean square criterion; stopping iteration until an residual error is less than a set threshold value; and finally reconstructing an original multiband signal through pseudo inverse operation by utilizing the obtained complete support set. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method can achieve the analog reconstruction of the multiband signal based on compressed sensing.

Methods and systems are disclosed for adaptive compression is disclosed. The compression is adaptive based on one or more criteria related to the system, including but not limited to: the centralized authority, one or more remote devices, the communication channel, and / or the data communicated. For example, the compression may be adaptive based on one or more criteria related to the remote device, including dynamic and / or static criteria of the remote device. In this way, the adaptive compression may be reduce the amount of data transmitted from the remote device to the centralized authority, thereby conserving bandwidth.

A compression subsystem for a computed tomography system compresses projection data to for efficient data transfer and storage. The compression includes applying an attenuation profile to an array of projection data samples. The attenuation profile is a function of sample coordinates and determines attenuation values applied to the samples. The attenuated samples are encoded and packed for data transfer. Alternatively, difference operators are applied to the attenuated samples and the differences are encoded. The average number of bits per compressed sample is monitored and the attenuation profiles can be modified to achieve a desired number of bits per compressed sample. The compressed samples are decompressed prior to image reconstruction processing. Decompression includes decoding the compressed samples and applying a gain profile to the decoded samples to restore the original dynamic range. This abstract does not limit the scope of the invention as described in the claims.

Systems, devices and methods for providing active and / or passive compression therapy to a body part can include a compression device worn over a compression stocking. The compression device can have a pulley based drive train that is driven by a motor to tighten and loosen compression elements, such as compression straps, in a precise, rapid, and balanced manner. Sensors can be used in the compression device and / or compression stockings to provide feedback to modulate the compression treatment parameters.

A method, data processing system, and computer program product for managing images. A processor unit divides an image for a virtual machine into blocks. The processor unit determines whether to compress the blocks prior to transmitting the blocks to a destination for the image. In response to a determination to compress the blocks, the processor unit compresses the blocks to form a compressed set of blocks. The processor unit sends the compressed set of blocks and any uncompressed blocks remaining in the blocks to the destination for the image.

A fuel cell system having an adaptable compressor map and method for optimizing the adaptable compressor map is provided. The method includes the steps of establishing an initial operating setpoint for an air compressor based on the adaptable compressor map; monitoring a surge indicator; adjusting the adaptable compressor map based on the monitored surge indicator; determining a desired operating setpoint based on the adjusted adaptable compressor map; and establishing an adapted operating setpoint for the air compressor based on the adaptable compressor map following the adjustment thereof. The steps are repeated until the adaptable compressor map for the air compressor is optimized.

Methods and systems for adaptive compression include compressing input data according to a first compression ratio; pausing compression after a predetermined amount of input data is compressed; estimating which of a set of ranges a compressed output size will fall within using current settings; and performing compression on a remainder of the input data according to a second compression ratio based on the estimated range.