| Patent application number | Description | Published |
|---|
| 20080247659 | Universal-denoiser context-modeling component and context-modeling method - In various embodiments of the present invention, a context-based denoiser is applied to each noisy-image symbol embedded within a context to determine a replacement symbol for the noisy-signal symbol. The context-based denoiser includes a context-modeling component that efficiently generates context classes and symbol-prediction classes, assigns individual contexts to context classes and symbol-prediction classes, collects symbol-occurrence statistics related to the generated context classes and symbol-prediction classes, and, optionally, generates noisy-symbol predictions. | 10-09-2008 |
| 20090037795 | Denoising and Error Correction for Finite Input, General Output Channel - 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. | 02-05-2009 |
| 20090112897 | DATA SEQUENCE COMPRESSION - In a method of compressing a data sequence, the data sequence is parsed into data segments, where at least one of the data segments includes a match. In addition, the match is compressed using at least one context model that depends upon one or more coded data symbols that are available to a decoder. An encoder includes a coding unit configured to code at least one of a match offset and a match length of a data segment using one or more context models that depend on previously decodeable data symbols. A computer readable storage medium having a computer program for implementing the method of compressing the data sequence. | 04-30-2009 |
| 20100278447 | Method and system for adaptive context-embedded prediction - One embodiment of the present invention is directed to an adaptive context-based predictor that predicts a value {circumflex over (x)} from a context, stored in an electronic memory, corresponding to a noisy-dataset symbol z | 11-04-2010 |
| 20110026848 | METHOD AND SYSTEM FOR ROBUST UNIVERSAL DENOISING OF NOISY DATA SETS - Embodiments of the present invention provide context-class-based universal denoising of noisy images and other noise-corrupted data sets. Prediction-error statistics for each prediction class, relative to a prefiltered image, are collected to estimate a bias for each prediction class, and prediction-error statistics for each conditioning class, relative to a prefiltered image, are accumulated based on the difference between predicted values and corresponding prefiltered-image symbols. The prediction-error statistics are accumulated using computed prediction-error-statistics vectors, with inversion of a prediction-error vector generated from each prediction prior to accumulation in a prediction-error-statistics vector. Conditional probability distributions are computed for individual contexts, which allow for computing a clean-image-estimated, value for each noisy-image value by minimizing a computed distortion over a range of possible estimated-clean-image symbols. | 02-03-2011 |
| 20110026850 | CONTEXT-CLUSTER-LEVEL CONTROL OF FILTERING ITERATIONS IN AN ITERATIVE DISCRETE UNIVERSAL DENOISER - Embodiments of the present invention are directed to various enhanced discrete-universal denoisers that have been developed to denoise images and other one-dimensional, two-dimensional or higher-dimensional data sets in which the frequency of occurrence of individual contexts may be too low to gather efficient statistical data or context-based symbol prediction. In these denoisers, image quality, signal-to-noise ratios, or other measures of the effectiveness of denoising that would be expected to increase monotonically over a series of iterations may decrease, due to assumptions underlying the discrete-universal-denoising method losing validity. Embodiments of the present invention apply context-class-based statistics and statistical analysis to determine, on a per-context-class basis, when to at least temporarily terminate denoising iterations on each conditioning class. Each iteration of the iterative methods applies context-based denoising only for those conditioning classes that statistical analysis indicates remain valid for denoising purposes. | 02-03-2011 |
| 20110129046 | DISCRETE DENOISING USING BLENDED COUNTS - Various embodiments of the present invention relate to a discrete denoiser that replaces symbols in a received, noisy signal with replacement symbols in order to produce a recovered signal less distorted with respect to an originally transmitted, clean signal than the received, noisy signal. Certain, initially developed discrete denoisers employ an analysis of the number of occurrences of metasymbols within the received, noisy signal in order to select symbols for replacement, and to select the replacement symbols for the symbols that are replaced. Denoisers that represent examples of the present invention use blended counts that are combinations of the occurrences of metasymbol families within a noisy signal to determine the symbols to be replaced and the replacement symbols corresponding to them. | 06-02-2011 |
| 20110242522 | DETERMINING DISTANCE BETWEEN NODES - A first node in a wireless network transmits a periodic pilot signal to a second node. The second node receives the periodic pilot signal and retransmits the signal back to the first node. The retransmitted pilot signal includes a phase adjustment in view of an internal processing delay at the second node. The phase adjustment involves matching a phase of the retransmitted pilot signal to a phase of the received pilot signal. The first node measures a roundtrip delay of the pilot signal and the distance between the nodes is computed based at least on the measured roundtrip delay. | 10-06-2011 |
