375 results about "Huffman coding" patented technology

Techniques like Huffman coding can be used to represent digital audio signal components more efficiently using non-uniform length symbols than can be represented by other coding techniques using uniform length symbols Unfortunately, the coding efficiency that can be achieved by Huffman coding depends on the probability density function of the information to be coded and the Huffman coding process itself requires considerable processing and memory resources. A coding process that uses gain-adaptive quantization according to the present invention can realize the advantage of using non-uniform length symbols while overcoming the shortcomings of Huffman coding. In gain-adaptive quantization, the magnitudes of signal components to be encoded are compared to one or more thresholds and placed into classes according to the results of the comparison. The magnitudes of the components placed into one of the classes are modified according to a gain factor that is related to the threshold used to classify the components. Preferably, the gain factor may be expressed as a function of only the threshold value. Gain-adaptive quantization may be used to encode frequency subband signals in split-band audio coding systems. Additional features including cascaded gain-adaptive quantization, intra-frame coding, split-interval and non-overloading quantizers are disclosed.

An audio encoder performs adaptive entropy encoding of audio data. For example, an audio encoder switches between variable dimension vector Huffman coding of direct levels of quantized audio data and run-level coding of run lengths and levels of quantized audio data. The encoder can use, for example, context-based arithmetic coding for coding run lengths and levels. The encoder can determine when to switch between coding modes by counting consecutive coefficients having a predominant value (e.g., zero). An audio decoder performs corresponding adaptive entropy decoding.

Systems, methods and computer accessible medium are provided through which an input data stream consisting one or more media regions before entering a network to be rendered by a display coupled a remote video frame buffer is compressed on the basis of one or more configuration file metadata, source primitive metadata, and application high-level metadata of identified media regions. The input data stream is compressed by using one or more MPEG compression, JPEG compression, vector graphics compression, Huffman coding, or user defined compression scheme.

Systems, methods and computer accessible medium are provided through which an input data stream consisting one or more media regions before entering a network to be rendered by a display coupled a remote video frame buffer is compressed on the basis of one or more configuration file metadata, source primitive metadata, and application high-level metadata of identified media regions. The input data stream is compressed by using one or more MPEG compression, JPEG compression, vector graphics compression, Huffman coding, or user defined compression scheme.

A method and system for coding audio signals in a multi-channel sound system, wherein a plurality of MDCT units are used to reduce the audio signals for providing a plurality of MDCT coefficients. The MDCT coefficients are quantized according to the masking threshold calculated from a psychoacoustic model and a plurality of INT (integer-to-integer) DCT modules are used to remove the cross-channel redundancy in the quantized MDCT coefficients. The output from the INT-DCT modules is Huffman coded and written to a bitstream for transmission or storage.

Methods, devices, and systems for coding and decoding audio are disclosed. Digital samples of an audio signal are transformed from the time domain to the frequency domain. The resulting transform coefficients are coded with a fast lattice vector quantizer. The quantizer has a high rate quantizer and a low rate quantizer. The high rate quantizer includes a scheme to truncate the lattice. The low rate quantizer includes a table based searching method. The low rate quantizer may also include a table based indexing scheme. The high rate quantizer may further include Huffman coding for the quantization indices of transform coefficients to improve the quantizing / coding efficiency.

This invention generates target encoded data by suppressing an arithmetic precision drop by executing processes such as orthogonal transformation and the like using the number of bits of an input image in place of reducing the number of bits at the time of input upon encoding an image. Upon generating baseline JPEG encoded data, a quantization table for an 8-bit image is stored in a quantization table storage unit. When an interpreter outputs information indicating that each color component per pixel of input image data is 16 bits, a bit shift unit multiplies the quantization table stored in the quantization table storage unit by the 8th power of 2 or {8th power of 2+1}. A quantizer quantizes coefficients output from a DCT unit on the basis of the quantization table stored in the quantization table storage unit, and a Huffman encoder encodes the quantization result to Huffman codes. A header is created by setting information indicating baseline JPEG and the quantization table stored in the quantization table storage unit, thus generating encoded data.

The invention provides an object and fractal-based binocular three-dimensional video compression and decompression method. In binocular three-dimensional video coding, a left channel is used as a basic layer, a right channel is used as an enhancement layer, and the left channel is encoded by an independent motion compensation prediction (MCP) mode. The object and fractal-based binocular three-dimensional video compression coding method comprises the following steps of: firstly, acquiring a video object partition plane, namely an Alpha plane by a video partition method, encoding the initial frame of a left eye through block discrete cosine transformation (DCT), and performing block motion estimation / compensation coding on a non-I frame of the left eye; secondly, determining the area attribute of an image block by utilizing the Alpha plane, and if the block is not within a video object area of the current code, not processing an external block, and if the block is within the video object area of the current code completely, searching the most similar matching block by a full-searching method in a previous frame of an internal block, namely a reference frame searching window of a left eye video; and finally, compressing coefficients of an iterated function system by a Huffman coding method, and if part of pixels of the block are within the video object area of the current code, and the other part of pixels are not within the video object area of the current code, processing a boundary block independently. The right channel is encoded by a MCP mode and a disparity compensation prediction (DCP) mode, the MCP is similar to the processing of the left eye, and the block with the minimum error is used as a prediction result. When the DCP coding mode is performed, the polarization and directionality in a three-dimensional parallel camera structure are utilized fully.

The invention discloses a system and method for realizing parallel decompression of hardware. The system comprises a variable-length bit manipulation module, a Huffman table recovery module, a Huffman coding module and a decoding module, wherein the variable-length bit manipulation module is used for carrying out variable-length bit manipulation on to-be-decompressed data to acquire variable-length data; the Huffman table recovery module is used for recovering a Huffman table in accordance with the variable-length data; the Huffman coding module is used for executing Huffman coding in parallel in accordance with the Huffman table; and the decoding module is used for carrying out decoding in accordance with the Huffman coding result. According to the system and method for realizing the parallel decompression of hardware, an FPGA (field programmable gate array) is utilized to realize a Gzip decompressing function, a parallel decompression algorithm is utilized and a hardware circuit structure suitable for the algorithm is designed, thus improving the processing efficiency of the decompression greatly.

Methods and systems that leverage the advantages of Huffman coding to increase processing efficiency of a data-stream while simultaneously minimizing storage requirements are provided. Decoding efficiency and table storage requirements can be balanced to produce systems that can be adapted for use in high-end network infrastructure applications and for low-resourced portable consumer devices. The systems and methods are operative in decoding data streams using multi-symbol codes and sign information, including AAC and MP3 data streams. A hierarchical structure of tables is described as having primary tables, secondary tables, tertiary tables and so on. Optimization balances processing requirements, table storage requirements and the described systems and methods may be implemented on a variety of processing platforms.

A time-of-flight measuring device for performing a hardware-based high-speed data compression process before transferring the data from a signal recorder to a data processor is provided. A time-series digital signal recorded by a signal recorder is converted to a plurality of time-series digital signals by being divided into a bit string including baseline information and a bit string not including the baseline information. Then, the time-series digital signal consisting of a bit string not including the baseline information is compressed by run-length encoding, such as zero length encoding or switched run-length encoding. Subsequently, static Huffman coding is performed on each of the time-series digital signals to reduce the data amount.

An image representation format for representing a digital image comprises: image information stored as a bitstream representing sequential image blocks, each block comprising one or more components, each component comprising one or more data units and each data unit being represented as a Huffman-coded stream of coefficients of basis functions, wherein a zeroth order coefficient is represented as a difference to the previous zeroth order coefficient of the corresponding component, and a block information table, which comprises: indicators to the first coefficient of a specified order of each image block in said bitstream, information indicating the number of bits in the bitstream between adjacent coefficients of said specified order of the image block, and the zeroth order coefficient of at least the first data unit of each components said zeroth order coefficient being represented in a non-differential form.

A Demura data lossless compression method of an OLED screen comprises performing Demura data Huffman coding lossless compression for R, G, B. The data compression method comprises the steps of: analyzing the gray scale of the read Demura image data, and counting the frequency of occurrence of each gray scale; performing the construction of the Huffman tree according to the frequency of each gray scale sorted according to the current Demura image data; performing a binary Huffman encoding on the constructed Huffman tree; and replacing the corresponding gray scale value in the original Demura image data with a Huffman encoded value. The invention adopts Huffman coding lossless compression to ensure the accuracy requirement in the Deumra process. Due to the characteristics such as the particularity of Demura data, relatively concentrated gray scale distribution and a higher ratio of the gray scale data with high frequency, the compression ratio of the encoded data is relatively high, andthe cost is saved.