Hewlett-packard Development Company, L.p.

Lucent Technologies Inc.

Alcatel-lucent USA Inc.

Sergio Verdu

Marcelo Weinberger

Erik Ordentlich

Gadiel Seroussi

Itschak Weissman

Giovanni Motta

Angel Lozano

Gadlel Seroussi

Antonia Maria Tulino

Tsachy Weissman

Krishnamurthy Viswanathan

Erik Ordentilch

Krishnamurthy Vlswanathan

Itschak (Tsachy) Weissman

Systems and methods are disclosed for denoising for a finite input, general output channel. In one aspect, a system is provided for processing a noisy signal formed by a noise-introducing channel in response to an error correction coded input signal, the noisy signal having symbols of a general alphabet. The system comprises a denoiser and an error correction decoder. The denoiser generates reliability information corresponding to metasymbols in the noisy signal based on an estimate of the distribution of metasymbols in the input signal and upon symbol transition probabilities of symbols in the input signal being altered in a quantized signal. A portion of each metasymbol provides a context for a symbol of the metasymbol. The quantized signal includes symbols of a finite alphabet and is formed by quantizing the noisy signal. The error correction decoder performs error correction decoding on noisy signal using the reliability information generated by the denoiser.

Denoising and error correction for finite input, general output channel

Systems and methods for iterative denoising and error correction decoding are presented. In an embodiment, a system iteratively processes a noisy signal formed by a noise-introducing channel in response to an error correction coded input signal. A denoiser generates reliability information for symbols in the input signal. The reliability information is generated by forming a product of received reliability information and an estimate of the distribution of metasymbols in the input signal, each metasymbol includes context symbols and a corresponding input symbol, and summing over values for the context symbols corresponding to the particular input symbol. An error correction decoder performs error correction decoding using the generated reliability information. In another embodiment, the reliability information is generated by forming a hard-decision decoded signal from received reliability information, determining metasymbol counts from the hard-decision decoded signal and solving an equation whose coefficients are obtained from the received reliability information and the metasymbol counts.

System and method for iterative denoising and error correction decoding

A method and apparatus for processing a received digital signal that has been corrupted by a channel is disclosed. The method includes storing the received digital signal and receiving a partially corrected sequence of symbols that includes an output of a preliminary denoising system operating on the received digital signal. Information specifying a signal degradation function that measures the signal degradation that occurs if a symbol having the value I is replaced by a symbol having the value J is utilized to generate a processed digital signal by replacing each symbol having a value I in a context of that symbol in the received digital signal with a symbol having a value J if replacement reduces a measure of overall signal degradation in the processed digital signal relative to the received digital signal as measured by the degradation function and the partially corrected sequence of symbols.

Enhanced denoising system

Various embodiments of the present invention provide methods and systems for determining, representing, and using variable-length contexts in a variety of different computational applications. In one embodiment of the present invention, a balanced tree is used to represent all possible contexts of a fixed length, where the depth of the balanced tree is equal to the fixed length of the considered contexts. Then, in the embodiment, a pruning technique is used to sequentially coalesce the children of particular nodes in the tree in order to produce an unbalanced tree representing a set of variable-length contexts. The pruning method is selected, in one embodiment, to coalesce nodes, and, by doing so, to truncate the tree according to statistical considerations in order to produce a representation of a variably sized context model suitable for a particular application.

Method and system for producing variable length context models

Denoising such as discrete universal denoising (DUDE) that scans a noisy signal in an attempt to characterize probabilities of finding symbol values in a particular context in a clean signal can perform a rough denoising on the noisy signal and identify contexts from a roughly denoised signal. The rough denoising improves estimation of the statistical properties of the clean signal by reducing the false differentiation of contexts that noise can otherwise create. Statistical information regarding occurrences of symbols in the noisy signal and corresponding contexts in the roughly denoised signal can then be used to denoise the noisy signal. The specifics of the rough denoising can be chosen based on knowledge of the noise or of the clean data. Alternatively, the DUDE can be used in an iterative fashion where the denoised signal produced from a prior iteration provides the contexts for the next iteration.

Context identification using a denoised signal

In one embodiment, the power for transmitting signals over at least one of a plurality of parallel channels is allocated based on a channel strength threshold and an estimated channel strength for the at least one channel. Here, the channel strength threshold is based on the estimated channel strengths for the plurality of channels.

Method of allocating power over channels of a communication system

Various embodiments of the present invention provide a compression method and system that compresses received data by first denoising the data and then losslessly compressing the denoised data. Denoising removes high entropy features of the data to produce lower entropy, denoised data that can be efficiently compressed by a lossless compression technique. One embodiment of the invention is a universal lossy compression method obtained by cascading a denoising technique with a universal lossless compression method. Alternative embodiments include methods obtained by cascading a denoising technique with one or more lossy or lossless compression methods.

Methods for compression using a denoiser

In various embodiments of the present invention, a noisy signal denoiser is tuned and optimized by selecting denoiser parameters that provide relatively highly compressible denoiser output. When the original signal can be compared to the output of a denoiser, the denoiser can be accurately tuned and adjusted in order to produce a denoised signal that resembles as closely as possible the clear signal originally transmitted through a noise-introducing channel. However, when the clear signal is not available, as in many communications applications, other methods are needed. By adjusting the parameters to provide a denoised signal that is globally or locally maximally compressible, the denoiser can be optimized despite inaccessibility of the original, clear signal.

Method and system for optimizing denoising parameters using compressibility

An apparatus for operating on a received signal that includes a noise-free signal that has been corrupted by a channel is disclosed. A memory stores a channel corruption function specifying the probability that a symbol having a value I was converted to a symbol having a value J by the channel, and a degradation function measuring the signal degradation that occurs if a symbol having the value I is replaced by symbol having a value J. The controller parses one of the received signal or the processed signal into phrases, and replaces one of the symbol having a value I in a context of that symbol in the received signal with a symbol having a value J if the replacement would reduce the estimated overall signal degradation in the processed signal. The context of a symbol depends on the phrase associated with the symbol.

Enhanced denoising system utilizing incremental parsing

A denoising process statistically processes a series of frames of a motion picture to construct respective data structures for the frames. Each data structure indicates for each of multiple contexts, occurrences of symbols that have the same context and are in the corresponding one of the frames. The data structures for multiple frames are combined to construct an enhanced data structure for one of the frames, and symbols in that frame are replaced with values determined using the enhanced data structure.

Denoising video

A discrete, universal denoising method is applied to a noisy signal for which the source alphabet is typically large. The method exploits a priori information regarding expected characteristics of the signal. In particular, using characteristics of a continuous tone image such as continuity and small-scale symmetry allows definition of context classes containing large numbers of image contexts having similar statistical characteristics. Use of the context classes allows extraction of more reliable indications of the characteristic of a clean signal.

Context-based denoiser that simultaneously updates probabilities for multiple contexts

A method of and system for generating reliability information for a noisy signal received through a noise-introducing channel. In one embodiment, symbol-transition probabilities are determined for the noise-introducing channel. Occurrences of metasymbols in the noisy signal are counted, each metasymbol providing a context for a symbol of the metasymbol. For each metasymbol occurring in the noisy signal, reliability information for each possible value of the symbol of the metasymbol is determined, the reliability information representing a probability that the value in the original signal corresponding to the symbol of the metasymbol assumed each of the possible values. In another embodiment, error correction coding may be performed by adding redundant data to an original signal prior to transmission by the noise-introducing channel and performing error correction decoding after transmission.

Discrete universal denoising with reliability information

In the method, spatial steering of parallel symbol streams and a transmit power of each symbol stream is determined based on a statistical distribution of a channel. The determined spatial steering and transmit powers may then be applied by a transmitter to optimize the transmit signal.

Method for optimizing the transmit signal in multiple antenna wireless links

An apparatus and method for processing a received signal that has been corrupted by a channel to generate a processed signal having less signal corruption than the received signal is disclosed. The apparatus stores the received signal, information specifying the probability that a symbol having a value I will be converted to a symbol having a value J by the channel, and information specifying a signal degradation function that measures the signal degradation that occurs if a symbol having the value I is replaced by symbol having a value J. The controller replaces each symbol having a value I in a context of that symbol in the received signal with a symbol having a value J that minimizes the overall signal degradation in the processed signal relative to the underlying noise-free signal as estimated via the observed statistics within that context.

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Princeton, NJ, United States of America

Sergio Verdu