self orthogonality of q ary images of q m ary codes and quantum code construction a code over gf can be imaged or expanded into a code over gf using a basis for the extension field over the base field the properties of such an image depend on the original code and the basis chosen for imaging problems relating the properties of a code and its image with respect to a basis have been of great interest in the field of coding theory in this work a generalized version of the problem of self orthogonality of the q ary image of a qm ary code has been considered given an inner product more generally a bi additive form necessary and sufficient conditions have been derived for a code over a field extension and an expansion basis so that an image of that code is self orthogonal the conditions require that the original code be self orthogonal with respect to several related bi additive forms whenever certain power sums of the dual basis elements do not vanish numerous interesting corollaries have been derived by specializing the general conditions an interesting result for the canonical or regular inner product in fields of characteristic two is that only self orthogonal codes result in self orthogonal images another result is that image of a code is self orthogonal for all bases if and only if trace of the code is self orthogonal except for the case of binary images of 4 ary codes the conditions are particularly simple to state and apply for cyclic codes to illustrate a possible application new quantum error correcting codes have been constructed with larger minimum distance than previously known

scale space and edge detection using anisotropic diffusion a new definition of scale space is suggested and a class of algorithms used to realize a diffusion process is introduced the diffusion coefficient is chosen to vary spatially in such a way as to encourage intraregion smoothing rather than interregion smoothing it is shown that the no new maxima should be generated at coarse scales property of conventional scale space is preserved as the region boundaries in the approach remain sharp a high quality edge detector which successfully exploits global information is obtained experimental results are shown on a number of images parallel hardware implementations are made feasible because the algorithm involves elementary local operations replicated over the image

speech intelligibility as a function of the number of channels of stimulation for signal processors using sine wave and noise band outputs vowels consonants and sentences were processed through software emulations of cochlear implant signal processors with 2 9 output channels the signals were then presented as either the sum of sine waves at the center of the channels or as the sum of noise bands the width of the channels to normal hearing listeners for identification the results indicate as previous investigations have suggested that high levels of speech understanding can be obtained using signal processors with a small number of channels the number of channels needed for high levels of performance varied with the nature of the test material for the most difficult material vowels produced by men women and girls no statistically significant differences in performance were observed when the number of channels was increased beyond 8 for the least difficult material sentences no statistically significant differences in performance were observed when the number of channels was increased beyond 5 the nature of the output signal noise bands or sine waves made only a small difference in performance the mechanism mediating the high levels of speech recognition achieved with only few channels of stimulation may be the same one that mediates the recognition of signals produced by speakers with a high fundamental frequency i e the levels of adjacent channels are used to determine the frequency of the input signal the results of an experiment in which frequency information was altered but temporal information was not altered indicates that vowel recognition is based on information in the frequency domain even when the number of channels of stimulation is small

iterative decoding of one step majority logic deductible codes based on belief propagation previously the belief propagation bp algorithm has received a lot of attention in the coding community mostly due to its near optimum decoding for low density parity check ldpc codes and its connection to turbo decoding in this paper we investigate the performance achieved by the bp algorithm for decoding one step majority logic decodable osmld codes the bp algorithm is expressed in terms of likelihood ratios rather than probabilities as conventionally presented the proposed algorithm fits better the decoding of osmld codes with respect to its numerical stability due to the fact that the weights of their check sums are often much higher than that of the corresponding ldpc codes although it has been believed that osmld codes are far inferior to ldpc codes we show that for medium code lengths say between 200 1000 bits the bp decoding of osmld codes can significantly outperform bp decoding of their equivalent ldpc codes the reasons for this behavior are elaborated

speckle reducing anisotropic diffusion this paper provides the derivation of speckle reducing anisotropic diffusion srad a diffusion method tailored to ultrasonic and radar imaging applications srad is the edge sensitive diffusion for speckled images in the same way that conventional anisotropic diffusion is the edge sensitive diffusion for images corrupted with additive noise we first show that the lee and frost filters can be cast as partial differential equations and then we derive srad by allowing edge sensitive anisotropic diffusion within this context just as the lee 1980 1981 1986 and frost 1982 filters utilize the coefficient of variation in adaptive filtering srad exploits the instantaneous coefficient of variation which is shown to be a function of the local gradient magnitude and laplacian operators we validate the new algorithm using both synthetic and real linear scan ultrasonic imagery of the carotid artery we also demonstrate the algorithm performance with real sar data the performance measures obtained by means of computer simulation of carotid artery images are compared with three existing speckle reduction schemes in the presence of speckle noise speckle reducing anisotropic diffusion excels over the traditional speckle removal filters and over the conventional anisotropic diffusion method in terms of mean preservation variance reduction and edge localization

expander codes using expander graphs we construct a new family of asymptotically good linear error correcting codes these codes have linear time sequential decoding algorithms and logarithmic time parallel decoding algorithms that use a linear number of processors we present both randomized and explicit constructions of these codes experimental results demonstrate the good performance of the randomly chosen codes

effects of spectral smearing and temporal fine structure distortion on the fluctuating masker benefit for speech at a fixed signal to noise ratio normal hearing listeners receive less benefit from momentary dips in the level of a fluctuating masker for speech processed to degrade spectral detail or temporal fine structure tfs than for unprocessed speech this has been interpreted as evidence that the magnitude of the fluctuating masker benefit fmb reflects the ability to resolve spectral detail and tfs however the fmb for degraded speech is typically measured at a higher signal to noise ratio snr to yield performance similar to normal speech for the baseline stationary noise condition because the fmb decreases with increasing snr this snr difference might account for the reduction in fmb for degraded speech in this study the fmb for unprocessed and processed tfs removed or spectrally smeared speech was measured in a paradigm that adjusts word set size rather than snr to equate stationary noise performance across processing conditions compared at the same snr and percent correct level but with different set sizes processed and unprocessed stimuli yielded a similar fmb for four different fluctuating maskers speech modulated noise one opposite gender interfering talker two same gender interfering talkers and 16 hz interrupted noise these results suggest that for these maskers spectral or tfs distortions do not directly impair the ability to benefit from momentary dips in masker level

factors affecting masking release for speech in modulated noise for normal hearing and hearing impaired listeners the speech reception threshold for sentences in stationary noise and in several amplitude modulated noises was measured for 8 normal hearing listeners 29 sensorineural hearing impaired listeners and 16 normal hearing listeners with simulated hearing loss this approach makes it possible to determine whether the reduced benefit from masker modulations as often observed for hearing impaired listeners is due to a loss of signal audibility or due to suprathreshold deficits such as reduced spectral and temporal resolution which were measured in four separate psychophysical tasks results show that the reduced masking release can only partly be accounted for by reduced audibility and that when considering suprathreshold deficits the normal effects associated with a raised presentation level should be taken into account in this perspective reduced spectral resolution does not appear to qualify as an actual suprathreshold deficit while reduced temporal resolution does temporal resolution and age are shown to be the main factors governing masking release for speech in modulated noise accounting for more than half of the intersubject variance their influence appears to be related to the processing of mainly the higher stimulus frequencies results based on calculations of the speech intelligibility index in modulated noise confirm these conclusions

a doubly degenerate diffusion equation in multiplicative noise removal models abstract in this paper we consider the neumann problem of a doubly degenerate diffusion equation which is proposed to deal with multiplicative noise we prove the existence and the extremum principle of weak solutions for the problem

noise driven anisotropic diffusion filtering of mri a new filtering method to remove rician noise from magnetic resonance images is presented this filter relies on a robust estimation of the standard deviation of the noise and combines local linear minimum mean square error filters and partial differential equations for mri as the speckle reducing anisotropic diffusion did for ultrasound images the parameters of the filter are automatically chosen from the estimated noise this property improves the convergence rate of the diffusion while preserving contours leading to more robust and intuitive filtering the partial derivative equation of the filter is extended to a new matrix diffusion filter which allows a coherent diffusion based on the local structure of the image and on the corresponding oriented local standard deviations this new filter combines volumetric planar and linear components of the local image structure the numerical scheme is explained and visual and quantitative results on simulated and real data sets are presented in the experiments the new filter leads to the best results

temporal integration of forward masking in listeners having sensorineural hearing loss findings are described from three experiments that were designed to contrast estimates of auditory time and frequency analysis in highly practiced young adult subjects having sensorineural hearing loss of cochlear origin with subjects having normal hearing in one experiment pure tone detection threshold was measured for two durations of tones for the hearing impaired subjects smaller differences were found between thresholds for the two durations of tones than were found for the normally hearing subjects at test frequencies where the sensitivity loss was greatest in a subsequent forward masking experiment masked thresholds were obtained at 3 khz as a function of masker level at several masker durations the results indicated that for the range of values tested masked probe thresholds changed less as a function of masker duration for the hearing impaired subjects than for normally hearing subjects however forward masking grew as a function of masker level more steeply for the hearing impaired listeners than for the normally hearing listeners we believe that this result indicates abnormal temporal processing of sequential sounds in a third experiment psychophysical tuning curves were measured in a forward masking procedure for two maskers that differed in duration by approximately an order of magnitude again the hearing impaired subjects demonstrated less change in forward masking as a function of masker duration than normally hearing subjects further the sharpness of the tuning curves from the hearing impaired listeners was markedly reduced as compared to normal it is believed that the results reflect a disruption of the normal temporal and spectral representation of sounds in the hearing impaired subjects

phoneme recognition in vocoded maskers by normal hearing and aided hearing impaired listeners this study compared modulation benefit for phoneme recognition obtained by normal hearing nh and aided hearing impaired hi listeners consonant and vowel recognition scores were measured using nonsense syllables in the presence of a steady state noise and four vocoded speech maskers vocoded maskers were generated by modulating the steady state noise in either one or six frequency channels with the speech envelope extracted from the speech of either a single talker or a four talker babble aided hi listeners obtained lower consonant recognition scores than nh listeners in all masker conditions vowel recognition scores for aided hi listeners were comparable to nh scores except in the six channel vocoded masker conditions where they were relatively lower analysis using the extended speech intelligibility index developed by rhebergen versfeld and dreschler 2006 j acoust soc am 120 6 3988 3997 suggested that the signal to noise ratio deficit observed in aided hi listeners was largely due to uncompensated audibility loss there was no significant difference between modulation masking release obtained by nh and aided hi listeners for both consonant and vowel recognition

an improved decoding algorithm for finite geometry ldpc codes in this letter an improved bit flipping decoding algorithm for high rate finite geometry low density parity check fg ldpc codes is proposed both improvement in performance and reduction in decoding delay are observed by flipping multiple bits in each iteration our studies show that the proposed algorithm achieves an appealing tradeoff between performance and complexity for fg ldpc codes

oriented speckle reducing anisotropic diffusion ultrasound imaging systems provide the clinician with noninvasive low cost and real time images that can help them in diagnosis planning and therapy however although the human eye is able to derive the meaningful information from these images automatic processing is very difficult due to noise and artifacts present in the image the speckle reducing anisotropic diffusion filter was recently proposed to adapt the anisotropic diffusion filter to the characteristics of the speckle noise present in the ultrasound images and to facilitate automatic processing of images we analyze the properties of the numerical scheme associated with this filter using a semi explicit scheme we then extend the filter to a matrix anisotropic diffusion allowing different levels of filtering across the image contours and in the principal curvature directions we also show a relation between the local directional variance of the image intensity and the local geometry of the image which can justify the choice of the gradient and the principal curvature directions as a basis for the diffusion matrix finally different filtering techniques are compared on a 2 d synthetic image with two different levels of multiplicative noise and on a 3 d synthetic image of a y junction and the new filter is applied on a 3 d real ultrasound image of the liver

anisotropic diffusion filter with memory based on speckle statistics for ultrasound images ultrasound us imaging exhibits considerable difficulties for medical visual inspection and for development of automatic analysis methods due to speckle which negatively affects the perception of tissue boundaries and the performance of automatic segmentation methods with the aim of alleviating the effect of speckle many filtering techniques are usually considered as a preprocessing step prior to automatic analysis methods or visual inspection most of the state of the art filters try to reduce the speckle effect without considering its relevance for the characterization of tissue nature however the speckle phenomenon is the inherent response of echo signals in tissues and can provide important features for clinical purposes this loss of information is even magnified due to the iterative process of some speckle filters e g diffusion filters which tend to produce over filtering because of the progressive loss of relevant information for diagnostic purposes during the diffusion process in this paper we propose an anisotropic diffusion filter with a probabilistic driven memory mechanism to overcome the over filtering problem by following a tissue selective philosophy in particular we formulate the memory mechanism as a delay differential equation for the diffusion tensor whose behavior depends on the statistics of the tissues by accelerating the diffusion process in meaningless regions and including the memory effect in regions where relevant details should be preserved results both in synthetic and real us images support the inclusion of the probabilistic memory mechanism for maintaining clinical relevant structures which are removed by the state of the art filters

design of capacity approaching irregular low density parity check codes we design low density parity check ldpc codes that perform at rates extremely close to the shannon capacity the codes are built from highly irregular bipartite graphs with carefully chosen degree patterns on both sides our theoretical analysis of the codes is based on the work of richardson and urbanke see ibid vol 47 no 2 p 599 618 2000 assuming that the underlying communication channel is symmetric we prove that the probability densities at the message nodes of the graph possess a certain symmetry using this symmetry property we then show that under the assumption of no cycles the message densities always converge as the number of iterations tends to infinity furthermore we prove a stability condition which implies an upper bound on the fraction of errors that a belief propagation decoder can correct when applied to a code induced from a bipartite graph with a given degree distribution our codes are found by optimizing the degree structure of the underlying graphs we develop several strategies to perform this optimization we also present some simulation results for the codes found which show that the performance of the codes is very close to the asymptotic theoretical bounds

masking of speech by amplitude modulated noise the masking of speech by amplitude modulated and unmodulated speech spectrum noise has been evaluated by the measurement of monaural speech recognition in such noise on young and elderly subjects with normal hearing and elderly hearing impaired subjects with and without a hearing aid sinusoidal modulation with frequencies covering the range 2 100 hz as well as an irregular modulation generated by the sum of four sinusoids in random phase relation was used modulation degrees were 100 6 db and 12 db root mean square sound pressure level was equal for modulated and unmodulated maskers for the normal hearing subjects essentially all types of modulated noise provided some release of speech masking as compared to unmodulated noise sinusoidal modulation provided more release of masking than the irregular modulation the release of masking increased with modulation depth it is proposed that the number and duration of low level intervals are essential factors for the degree of masking the release of masking was found to reach a maximum at a modulation frequency between 10 and 20 hz for sinusoidal modulation for elderly hearing impaired subjects the release of masking obtained from amplitude modulation was consistently smaller than in the normal hearing groups presumably related to changes in auditory temporal resolution caused by the hearing loss the average speech to noise ratio required for 30 correct speech recognition varied greatly between the groups for young normal hearing subjects it was 15 db for elderly normal hearing it was 9 db for elderly hearing impaired subjects in the unaided listening condition it was 2 db and in the aided condition it was 3 db the results support the conclusion that within the methodological context of the study age as well as sensorineural hearing loss as such influence speech recognition in noise more than what can be explained by the loss of audibility according to the audiogram and the masking noise spectrum

speech perception in gated noise the effects of temporal resolution previous investigations have suggested that hearing impaired hi listeners have reduced masking release mr compared to normal hearing listeners nh when they listen in modulated noise the current study examined the following questions that have not been clearly answered first when hi listeners are amplified so that their performance is equal to that of nh listeners in quiet and in steady noise do hi listeners still show reduced mr with modulated noise when compared to nh listeners second is the masking release the same for sentences and cv syllables third does forward masking significantly contribute to the variability in performance among hi listeners to compensate for reduced hearing sensitivity for hi listeners the spectrum levels of both speech and noise were adjusted based on the individual hearing loss there was no significant difference between the performance of nh listeners and that of hi listeners in steady noise and in quiet however the amount of mr for sentences and for cv syllables was significantly reduced for hi listeners for sentence recognition the amount of mr seemed to be more related to hearing sensitivity for low to mid frequencies than to forward masking in contrast forward masking thresholds appear to be a major contributor to the amount of mr for syllable recognition

gaps in the binary weight distributions of reed solomon codes when a reed solomon code is expanded to form a binary code certain combinations of the spectrum of the reed solomon code and the basis used for the expansion result in large gaps in the weight distribution of the binary code it is shown that the size of these gaps can be bounded by computing the sums of various powers of the basis elements and applying a theorem normally used for cyclic codes this explains why codes obtained by using a polymomial basis often have smaller gaps in their weight distributions than those obtained by using a normal basis similar results apply to the number of intersections between codewords which can be used to show that the codewords are orthogonal

on the impact of anisotropic diffusion on edge detection content aware edge preserving smoothing techniques have gained visibility in recent years however they have had a rather limited impact on the edge detection literature compared to content unaware linear techniques often based on gaussian filters in this work we focus on anisotropic diffusion covering its initial definition by perona and malik and subsequent extensions a visual case study is used to illustrate their features we perform a quantitative evaluation of the performance of the canny method for edge detection when substituting linear gaussian smoothing filters by anisotropic diffusion highlightsreviewing the main trends in anisotropic diffusion identifying the practical scenarios on which anisotropic diffusion fails quantifying the improvement of edge detection when anisitropic diffusion is applied

rayleigh maximum likelihood filtering for speckle reduction of ultrasound images speckle is a multiplicative noise that degrades ultrasound images recent advancements in ultrasound instrumentation and portable ultrasound devices necessitate the need for more robust despeckling techniques for both routine clinical practice and teleconsultation methods previously proposed for speckle reduction suffer from two major limitations 1 noise attenuation is not sufficient especially in the smooth and background areas 2 existing methods do not sufficiently preserve or enhance edges they only inhibit smoothing near edges in this paper we propose a novel technique that is capable of reducing the speckle more effectively than previous methods and jointly enhancing the edge information rather than just inhibiting smoothing the proposed method utilizes the rayleigh distribution to model the speckle and adopts the robust maximum likelihood estimation approach the resulting estimator is statistically analyzed through first and second moment derivations a tuning parameter that naturally evolves in the estimation equation is analyzed and an adaptive method utilizing the instantaneous coefficient of variation is proposed to adjust this parameter to further tailor performance a weighted version of the proposed estimator is introduced to exploit varying statistics of input samples finally the proposed method is evaluated and compared to well accepted methods through simulations utilizing synthetic and real ultrasound data

effects of inherent envelope fluctuations in forward maskers for listeners with normal and impaired hearing gaussian noise simultaneous maskers yield higher masked thresholds for pure tones than low fluctuation noise simultaneous maskers for listeners with normal hearing this increased masking effectiveness is thought to be due to inherent fluctuations in the temporal envelope of gaussian noise but effects of fluctuating forward maskers are unknown because differences in forward masking due to age and hearing loss are known the current study assessed effects of masker envelope fluctuations for forward maskers in younger and older adults with normal hearing and older adults with hearing loss detection thresholds were measured in these three participant groups for a pure tone probe in quiet and in gaussian and low fluctuation noise forward maskers with either 1 or 1 3 equivalent rectangular bandwidths higher masked thresholds were obtained for forward maskers with greater inherent envelope fluctuations for younger adults with normal hearing this increased effectiveness of highly fluctuating forward maskers was similar for older adults with normal and impaired hearing because differences in recovery from forward masking between listeners with normal and impaired hearing may relate to differences in cochlear nonlinearities these results suggest that mechanisms other than cochlear nonlinearities may be responsible for recovery from rapid masker envelope fluctuations

hyperconnected attribute filters based on k flat zones in this paper we present a new method for attribute filtering combining contrast and structural information using hyperconnectivity based on k flat zones we improve the ability of attribute filters to retain internal details in detected objects simultaneously we improve the suppression of small unwanted detail in the background we extend the theory of attribute filters to hyperconnectivity and provide a fast algorithm to implement the new method the new version is only marginally slower than the standard max tree algorithm for connected attribute filters and linear in the number of pixels or voxels it is two orders of magnitude faster than anisotropic diffusion the method is implemented in the form of a filtering rule suitable for handling both increasing size and nonincreasing shape attributes we test this new framework on nonincreasing shape filters on both 2d images from astronomy document processing and microscopy and 3d ct scans and show increased robustness to noise while maintaining the advantages of previous methods

temporal masking functions for listeners with real and simulated hearing loss a functional simulation of hearing loss was evaluated in its ability to reproduce the temporal masking functions for eight listeners with mild to severe sensorineural hearing loss each audiometric loss was simulated in a group of age matched normal hearing listeners through a combination of spectrally shaped masking noise and multi band expansion temporal masking functions were obtained in both groups of listeners using a forward masking paradigm in which the level of a 110 ms masker required to just mask a 10 ms fixed level probe 5 10 db sl was measured as a function of the time delay between the masker offset and probe onset at each of four probe frequencies 500 1000 2000 and 4000 hz temporal masking functions were obtained using maskers that were 0 55 1 0 and 1 15 times the probe frequency the slopes and y intercepts of the masking functions were not significantly different for listeners with real and simulated hearing loss the y intercepts were positively correlated with level of hearing loss while the slopes were negatively correlated the ratio of the slopes obtained with the low frequency maskers relative to the on frequency maskers was similar for both groups of listeners and indicated a smaller compressive effect than that observed in normal hearing listeners

the existence of binary linear concatenated codes with reed solomon outer codes which asymptotically meet the gilbert varshamov bound binary linear concatenated codes with reed solomon codes as the outer code and varying nonsystematic inner codes are investigated it is shown that codes exist in this class which asymptotically meet the gilbert varshamov bound

hard and soft decision decoding beyond the half minimum distance an algorithm for linear codes corresp a decoding algorithm for linear codes that uses the minimum weight words of the dual code as parity checks is defined this algorithm is able to correct beyond the half minimum distance and has the capability of including soft decision decoding results on applying this algorithm to quadratic residue qr codes bch codes and the golay codes with and without soft decision decoding are presented

improved decoding of reed solomon and algebraic geometry codes given an error correcting code over strings of length n and an arbitrary input string also of length n the list decoding problem is that of finding all codewords within a specified hamming distance from the input string we present an improved list decoding algorithm for decoding reed solomon codes the list decoding problem for reed solomon codes reduces to the following curve fitting problem over a field f given n points x sub i spl middot y sub i sub i 1 sup n x sub i y sub i spl isin f and a degree parameter k and error parameter e find all univariate polynomials p of degree at most k such that y sub i p x sub i for all but at most e values of i spl isin 1 n we give an algorithm that solves this problem for e 1 3 where the result yields the first asymptotic improvement in four decades the algorithm generalizes to solve the list decoding problem for other algebraic codes specifically alternant codes a class of codes including bch codes and algebraic geometry codes in both cases we obtain a list decoding algorithm that corrects up to n spl radic n n d errors where n is the block length and d is the designed distance of the code the improvement for the case of algebraic geometry codes extends the methods of shokrollahi and wasserman see in proc 29th annu acm symp theory of computing p 241 48 1998 and improves upon their bound for every choice of n and d we also present some other consequences of our algorithm including a solution to a weighted curve fitting problem which may be of use in soft decision decoding algorithms for reed solomon codes

a behavioral measure of basilar membrane nonlinearity in listeners with normal and impaired hearing this paper examines the possibility of estimating basilar membrane bm nonlinearity using a psychophysical technique the level of a forward masker required to mask a brief signal was measured for conditions where the masker was either at or one octave below the signal frequency the level of the forward masker at masked threshold provided an indirect measure of the bm response to the signal as follows consistent with physiological studies it was assumed that the bm responds linearly to frequencies well below the characteristic frequency cf thus the ratio of the slopes of the masking functions between a masker at the signal frequency and a masker well below the signal frequency should provide an estimate of bm compression at cf results obtained from normally hearing listeners were in quantitative agreement with physiological estimates of bm compression furthermore differences between normally hearing listeners and listeners with cochlear hearing impairment were consistent with the physiological effects of damage to the cochlea the results support the hypothesis that bm nonlinearity governs the nonlinear growth of the upward spread of masking and suggest that this technique provides a straightforward method for estimating bm nonlinearity in humans

edge detection in ultrasound imagery using the instantaneous coefficient of variation the instantaneous coefficient of variation icov edge detector based on normalized gradient and laplacian operators has been proposed for edge detection in ultrasound images in this paper the edge detection and localization performance of the icov squared icovs detector are examined first a simplified version of the icovs detector the normalized gradient magnitude squared is scrutinized in order to reveal the statistical performance of edge detection and localization in speckled ultrasound imagery both the probability of detection and the probability of false alarm are evaluated for the detector edge localization is characterized by the position of the peak and the 3 db width of the detector response then the speckle edge response of the icovs as applied to a realistic edge model is studied through theoretical analysis we reveal the compensatory effects of the normalized laplacian operator in the icov edge detector for edge localization error an icov based edge detection algorithm is implemented in which the icov detector is embedded in a diffusion coefficient in an anisotropic diffusion process experiments with real ultrasound images have shown that the proposed algorithm is effective in extracting edges in the presence of speckle quantitatively the icovs provides a lower localization error and qualitatively a dramatic improvement in edge detection performance over an existing edge detection method for speckled imagery

ldpc codes from generalized polygons we use the theory of finite classical generalized polygons to derive and study low density parity check ldpc codes the tanner graph of a generalized polygon ldpc code is highly symmetric inherits the diameter size of the parent generalized polygon and has minimum one half diameter to girth ratio we show formally that when the diameter is four or six or eight all codewords have even hamming weight when the generalized polygon has in addition an equal number of points and lines we see that the nonregular polygon based code construction has minimum distance that is higher at least by two in comparison with the dual regular polygon code of the same rate and length a new minimum distance bound is presented for codes from nonregular polygons of even diameter and equal number of points and lines finally we prove that all codes derived from finite classical generalized quadrangles are quasi cyclic and we give the explicit size of the circulant blocks in the parity check matrix our simulation studies of several generalized polygon ldpc codes demonstrate powerful bit error rate ber performance when decoding is carried out via low complexity variants of belief propagation

joint image denoising using adaptive principal component analysis and self similarity the non local means nlm has attracted enormous interest in image denoising problem in recent years in this paper we propose an efficient joint denoising algorithm based on adaptive principal component analysis pca and self similarity that improves the predictability of pixel intensities in reconstructed images the proposed algorithm consists of two successive steps without iteration the low rank approximation based on parallel analysis and the collaborative filtering first for a pixel and its nearest neighbors the training samples in a local search window are selected to form the similar patch group by the block matching method next it is factorized by singular value decomposition svd whose left and right orthogonal basis denote local and non local image features respectively the adaptive pca automatically chooses the local signal subspace dimensionality of the noisy similar patch group in the svd domain by the refined parallel analysis with monte carlo simulation thus image features can be well preserved after dimensionality reduction and simultaneously the noise is almost eliminated then after the inverse svd transform the denoised image is reconstructed from the aggregate filtered patches by the weighted average method finally the collaborative wiener filtering is used to further remove the noise the experimental results validate its generality and effectiveness in a wide range of the noisy images the proposed algorithm not only produces very promising denoising results that outperforms the state of the art methods in most cases but also adapts to a variety of noise levels

near optimum universal belief propagation based decoding of low density parity check codes in this paper we propose a belief propagation bp based decoding algorithm which utilizes normalization to improve the accuracy of the soft values delivered by a previously proposed simplified bp based algorithm the normalization factors can be obtained not only by simulation but also importantly theoretically this new bp based algorithm is much simpler to implement than bp decoding as it requires only additions of the normalized received values and is universal i e the decoding is independent of the channel characteristics some simulation results are given which show this new decoding approach can achieve an error performance very close to that of bp on the additive white gaussian noise channel especially for low density parity check ldpc codes whose check sums have large weights the principle of normalization can also be used to improve the performance of the max log map algorithm in turbo decoding and some coding gain can be achieved if the code length is long enough

effect of amplitude modulation coherence for masked speech signals filtered into narrow bands introduction of masker amplitude modulation am can improve signal detection in a number of paradigms in some cases this advantage depends on the coherence of modulation across a relatively wide frequency range in the experiments described below observers were asked to identify masked spondee words produced by a single male talker the target spondees and masking noise were filtered into nine narrow bands and the coherence of am of either the speech signal or noise masker was manipulated inherent modulation of the masker bands was manipulated via assignment of real and imaginary values to the associated components of each band in the frequency domain and am of speech bands was achieved via multiplication with envelopes extracted from these maskers responses were based on two alternatives four alternatives or open response sets the effect of masker am coherence was highly dependent upon the size of the response set coherent am was associated with better thresholds in a two alternative response set but poorer thresholds in an open response set results with am speech did not depend critically upon the across frequency temporal synchrony of am imposed on the speech material

the average binary weight enumerator for a class of generalized reed solomon codes an explicit weight enumerator for the set of binary expansions of a class of generalized reed solomon codes is derived this enumerator is then used to show that most of these binary codes are asymptotically good and to bound the rates of self intersecting codes

probability density difference based active contour for ultrasound image segmentation because of its low signal noise ratio low contrast and blurry boundaries ultrasound us image segmentation is a difficult task in this paper a novel level set based active contour model is proposed for breast ultrasound bus image segmentation at first an energy function is formulated according to the differences between the actual and estimated probability densities of the intensities in different regions the actual probability densities are calculated directly for calculating the estimated probability densities the probability density estimation method and background knowledge are utilized the energy function is formulated with level set approach and a partial differential equation is derived for finding the minimum of the energy function for performing numerical computation the derived partial differential equation is approximated by the central difference and non re initialization approach the proposed method was operated on both the synthetic images and clinical bus images for studying its characteristics and evaluating its performance the experimental results demonstrate that the proposed method can model the bus images well be robust to noise and segment the bus images accurately and reliably

behavioral measures of cochlear compression and temporal resolution as predictors of speech masking release in hearing impaired listeners hearing impaired hi listeners often show less masking release mr than normal hearing listeners when temporal fluctuations are imposed on a steady state masker even when accounting for overall audibility differences this difference may be related to a loss of cochlear compression in hi listeners behavioral estimates of compression using temporal masking curves tmcs were compared with mr for band limited 500 4000 hz speech and pure tones in hi listeners and age matched noise masked normal hearing nmnh listeners compression and pure tone mr estimates were made at 500 1500 and 4000 hz the amount of mr was defined as the difference in performance between steady state and 10 hz square wave gated speech shaped noise in addition temporal resolution was estimated from the slope of the off frequency tmc no significant relationship was found between estimated cochlear compression and mr for either speech or pure tones nmnh listeners had significantly steeper off frequency temporal masking recovery slopes than did hi listeners and a small but significant correlation was observed between poorer temporal resolution and reduced mr for speech the results suggest either that the effects of hearing impairment on mr are not determined primarily by changes in peripheral compression or that the tmc does not provide a sufficiently reliable measure of cochlear compression

auditory filter characteristics and consonant recognition for hearing impaired listeners to examine the association between frequency resolution and speech recognition auditory filter parameters and stop consonant recognition were determined for 9 normal hearing and 24 hearing impaired subjects in an earlier investigation the relationship between stop consonant recognition and the articulation index ai had been established on normal hearing listeners based on ai predictions speech presentation levels for each subject in this experiment were selected to obtain a wide range of recognition scores this strategy provides a method of interpreting speech recognition performance among listeners who vary in magnitude and configuration of hearing loss by assuming that conditions which yield equal audible spectra will result in equivalent performance it was reasoned that an association between frequency resolution and consonant recognition may be more appropriately estimated if hearing impaired listeners performance was measured under conditions that assured equivalent audibility of the speech stimuli derived auditory filter parameters indicated that filter widths and dynamic ranges were strongly associated with threshold stop consonant recognition scores for most hearing impaired listeners were not significantly poorer than predicted by the ai model furthermore differences between observed recognition scores and those predicted by the ai were not associated with auditory filter characteristics suggesting that frequency resolution and speech recognition may appear to be associated primarily because both are degraded by threshold elevation

temporal resolution in sensorineural hearing impaired listeners temporal masking curves were obtained from 12 normal hearing and 16 hearing impaired listeners using 200 ms 1000 hz pure tone maskers and 20 ms 1000 hz fixed level probe tones for the delay times used here 40 ms temporal masking curves obtained from both groups can be well described by an exponential function with a single level independent time constant for each listener normal hearing listeners demonstrated time constants that ranged between 37 and 67 ms with a mean of 50 ms most hearing impaired listeners with significant hearing loss at the probe frequency demonstrated longer time constants range 58 114 ms than those obtained from normal hearing listeners time constants were found to grow exponentially with hearing loss according to the function 52e0 011 hl when the slope of the growth of masking is unity the longest individual time constant was larger than normal by a factor of 2 3 for a hearing loss of 52 db the steep slopes of the growth of masking functions typically observed

low density parity check codes based on finite geometries a rediscovery and new results this paper presents a geometric approach to the construction of low density parity check ldpc codes four classes of ldpc codes are constructed based on the lines and points of euclidean and projective geometries over finite fields codes of these four classes have good minimum distances and their tanner 1981 graphs have girth 6 finite geometry ldpc codes can be decoded in various ways ranging from low to high decoding complexity and from reasonably good to very good performance they perform very well with iterative decoding furthermore they can be put in either cyclic or quasi cyclic form consequently their encoding can be achieved in linear time and implemented with simple feedback shift registers this advantage is not shared by other ldpc codes in general and is important in practice finite geometry ldpc codes can be extended and shortened in various ways to obtain other good ldpc codes several techniques of extension and shortening are presented long extended finite geometry ldpc codes have been constructed and they achieve a performance only a few tenths of a decibel away from the shannon theoretical limit with iterative decoding

fractional subpixel diffusion and fuzzy logic approach for ultrasound speckle reduction speckle is the dominant source of noise in ultrasound imaging and is a kind of multiplicative noise it is difficult to design a filter to remove speckle effectively in this paper a novel fuzzy subpixel fractional partial difference fsfpd for ultrasound speckle reduction is proposed euler lagrange equation acts as an increasing function of the fractional derivative s absolute value of the image intensity function the fractional order partial difference is computed in the frequency and fuzzy domain with subpixel precision we test the proposed method on both synthetic and real breast ultrasound bus images the comparisons of the experimental results show that the proposed method can preserve edges and structural details of ultrasound images well while removing speckle noise in addition the filtered images are assessed and evaluated by radiologists using double blind method the results demonstrate that the discrimination rate of breast cancers has been highly improved after employing the proposed method

revision extension and evaluation of a binaural speech intelligibility model this study presents revision extension and evaluation of a binaural speech intelligibility model beutelmann r and brand t 2006 j acoust soc am 120 331 342 that yields accurate predictions of speech reception thresholds srts in the presence of a stationary noise source at arbitrary azimuths and in different rooms the modified model is based on an analytical expression of binaural unmasking for arbitrary input signals and is computationally more efficient while maintaining the prediction quality of the original model an extension for nonstationary interferers was realized by applying the model to short time frames of the input signals and averaging over the predicted srt results binaural srts from 8 normal hearing and 12 hearing impaired subjects incorporating all combinations of four rooms three source setups and three noise types were measured and compared to the model s predictions depending on the noise type the parametric correlation coefficients between observed and predicted srts were 0 80 0 93 for normal hearing subjects and 0 59 0 80 for hearing impaired subjects the mean absolute prediction error was 3 db for the mean normal hearing data and 4 db for the individual hearing impaired data 70 of the variance of the srts of hearing impaired subjects could be explained by the model which is based only on the audiogram

enclosure transform for interest point detection from speckle imagery we present a fast enclosure transform et to localize complex objects of interest from speckle imagery this approach explores the spatial confinement on regional features from a sparse image feature representation unrelated broken ridge features surrounding an object are organized collaboratively giving rise to the enclosureness of the object three enclosure likelihood measures are constructed consisting of the enclosure force potential energy and encloser count in the transform domain the local maxima manifest the locations of objects of interest for which only the intrinsic dimension is known a priori the discrete et algorithm is computationally efficient being on the order of o mn using n measuring distances across an image of m ridge pixels it involves easy and few parameter settings we demonstrate and assess the performance of et on the automatic detection of the prostate locations from supra pubic ultrasound images et yields superior results in terms of positive detection rate accuracy and coverage

ultrasound image despeckling using stochastic distance based bm3d ultrasound image despeckling is an important research field since it can improve the interpretability of one of the main categories of medical imaging many techniques have been tried over the years for ultrasound despeckling and more recently a great deal of attention has been focused on patch based methods such as non local means and block matching collaborative filtering bm3d a common idea in these recent methods is the measure of distance between patches originally proposed as the euclidean distance for filtering additive white gaussian noise in this paper we derive new stochastic distances for the fisher tippett distribution based on well known statistical divergences and use them as patch distance measures in a modified version of the bm3d algorithm for despeckling log compressed ultrasound images state of the art results in filtering simulated synthetic and real ultrasound images confirm the potential of the proposed approach

efficient iterative techniques for soft decision decoding of reed solomon codes two new iterative soft decision decoding methods for reed solomon rs codes are proposed these methods are based on bit level belief propagation bp decoding in order to make bp decoding effective for rs codes we use an extended binary parity check matrix with a lower density and reduced number of 4 cycles compared to the original binary parity check matrix of the code in the first proposed method we take advantage of the cyclic structure of rs codes based on this property we can apply the belief propagation algorithm on any cyclically shifted version of the received symbols with the same binary parity check matrix for each shifted version of received symbols the distribution of reliability values will change and deterministic errors can be avoided this method results in considerable performance improvement of rs codes compared to hard decision decoding the performance is also superior to some popular soft decision decoding methods the second method is based on information correction in bp decoding it means that we determine least reliable bits and by changing their channel information the convergence of the decoder is improved compared to the first method this method needs less bp iterations less complexity but its performance is not as good

nonlinear diffusion in laplacian pyramid domain for ultrasonic speckle reduction a new speckle reduction method i e laplacian pyramid based nonlinear diffusion lpnd is proposed for medical ultrasound imaging with this method speckle is removed by nonlinear diffusion filtering of bandpass ultrasound images in laplacian pyramid domain for nonlinear diffusion in each pyramid layer a gradient threshold is automatically determined by a variation of median absolute deviation mad estimator the performance of the proposed lpnd method has been compared with that of other speckle reduction methods including the recently proposed speckle reducing anisotropic diffusion srad and nonlinear coherent diffusion ncd in simulation and phantom studies an average gain of 1 55 db and 1 34 db in contrast to noise ratio was obtained compared to srad and ncd respectively the visual comparison of despeckled in vivo ultrasound images from liver and carotid artery shows that the proposed lpnd method could effectively preserve edges and detailed structures while thoroughly suppressing speckle these preliminary results indicate that the proposed speckle reduction method could improve image quality and the visibility of small structures and fine details in medical ultrasound imaging

pulse number discrimination by cope s gray treefrog hyla chrysoscelis in modulated and unmodulated noise in cope s gray treefrog hyla chrysoscelis thresholds for recognizing conspecific calls are lower in temporally modulated noise backgrounds compared with unmodulated noise the effect of modulated noise on discrimination among different conspecific calls is unknown in quiet females prefer calls with relatively more pulses this study tested the hypotheses that noise impairs selectivity for longer calls and that processes akin to dip listening in modulated noise can ameliorate this impairment in two stimulus choice tests female subjects were allowed to choose between an average length call and a shorter or longer alternative tests were replicated at two signal levels in quiet and in the presence of chorus shaped noise that was unmodulated modulated by a sinusoid or modulated by envelopes resembling natural choruses when subjects showed a preference it was always for the relatively longer call noise reduced preferences for longer calls but the magnitude of this reduction was unrelated to whether the noise envelope was modulated or unmodulated together the results are inconsistent with the hypothesis that dip listening improves a female gray treefrog s ability to select longer calls in modulated compared with unmodulated noise

higher order regularization based image restoration with automatic regularization parameter selection abstract poisson and multiplicative rayleigh noises often appear in medical imaging such as x ray images positron emission tomography and ultrasound images in this study we propose novel variational models for removing poisson multiplicative rayleigh noise we make use of hybrid higher order total variation as the regularization terms of our proposed models to eliminate staircasing artifacts we also adopt the spatially adaptive parameter technique to adequately smooth homogenous regions while preserving the edges the spatially adaptive parameter selection is closely related to local constraints through a local expected value estimator we provide a convergence analysis including the existence and uniqueness of solution and the first order optimality conditions we apply the alternating direction method of multipliers for solving the proposed models numerical experiments demonstrate that our models exhibit a better performance than that of state of the art models in terms of edge preservation smoothness of the homogenous regions and various quality measures

speech reception by listeners with real and simulated hearing impairment effects of continuous and interrupted noise the effects of audibility and age on masking for sentences in continuous and interrupted noise were examined in listeners with real and simulated hearing loss the absolute thresholds of each of ten listeners with sensorineural hearing loss were simulated in normal hearing listeners through a combination of spectrally shaped threshold noise and multi band expansion for octave bands with center frequencies from 0 25 8 khz each individual hearing loss was simulated in two groups of three normal hearing listeners an age matched and a non age matched group the speech to noise ratio s n for 50 correct identification of hearing in noise test hint sentences was measured in backgrounds of continuous and temporally modulated 10 hz square wave noise at two overall levels for unprocessed speech and for speech that was amplified with the nal rp prescription the s n in both continuous and interrupted noise of the hearing impaired listeners was relatively well simulated in both groups of normal hearing listeners thus release from masking the difference in s n obtained in continuous versus interrupted noise appears to be determined primarily by audibility minimal age effects were observed in this small sample observed values of masking release were compared to predictions derived from intelligibility curves generated using the extended speech intelligibility index esii rhebergen et al 2006 j acoust soc am 120 3988 3997

robust scale space filter using second order partial differential equations this paper describes a robust scale space filter that adaptively changes the amount of flux according to the local topology of the neighborhood in a manner similar to modeling heat or temperature flow in physics the robust scale space filter is derived by coupling fick s law with a generalized continuity equation in which the source or sink is modeled via a specific heat capacity the filter plays an essential part in two aspects first an evolution step size is adaptively scaled according to the local structure enabling the proposed filter to be numerically stable second the influence of outliers is reduced by adaptively compensating for the incoming flux we show that classical diffusion methods represent special cases of the proposed filter by analyzing the stability condition of the proposed filter we also verify that its evolution step size in an explicit scheme is larger than that of the diffusion methods the proposed filter also satisfies the maximum principle in the same manner as the diffusion our experimental results show that the proposed filter is less sensitive to the evolution step size as well as more robust to various outliers such as gaussian noise impulsive noise or a combination of the two

iterative decoding of binary block and convolutional codes iterative decoding of two dimensional systematic convolutional codes has been termed turbo de coding using log likelihood algebra we show that any decoder can be used which accepts soft inputs including a priori values and delivers soft outputs that can be split into three terms the soft channel and a priori inputs and the extrinsic value the extrinsic value is used as an a priori value for the next iteration decoding algorithms in the log likelihood domain are given not only for convolutional codes but also for any linear binary systematic block code the iteration is controlled by a stop criterion derived from cross entropy which results in a minimal number of iterations optimal and suboptimal decoders with reduced complexity are presented simulation results show that very simple component codes are sufficient block codes are appropriate for high rates and convolutional codes for lower rates less than 2 3 any combination of block and convolutional component codes is possible several interleaving techniques are described at a bit error rate ber of 10 sup 4 the performance is slightly above or around the bounds given by the cutoff rate for reasonably simple block convolutional component codes interleaver sizes less than 1000 and for three to six iterations

tracking pylorus in ultrasonic image sequences with edge based optical flow tracking pylorus in ultrasonic image sequences is an important step in the analysis of duodenogastric reflux dgr we propose a joint prediction and segmentation method jps which combines optical flow with active contour to track pylorus the goal of the proposed method is to improve the pyloric tracking accuracy by taking account of not only the connection information among edge points but also the spatio temporal information among consecutive frames the proposed method is compared with other four tracking methods by using both synthetic and real ultrasonic image sequences several numerical indexes hausdorff distance hd average distance ad mean edge distance med and edge curvature ec have been calculated to evaluate the performance of each method jps achieves the minimum distance metrics hd ad and med and a smaller ec the experimental results indicate that jps gives a better tracking performance than others by the best agreement with the gold curves while keeping the smoothness of the result

algebraic soft decision decoding of reed solomon codes using bit level soft information the performance of algebraic soft decision decoding of reed solomon codes using bit level soft information is investigated optimal multiplicity assignment strategies for algebraic soft decision decoding sdd with infinite cost are first studied over erasure channels and the binary symmetric channel the corresponding decoding radii are calculated in closed forms and tight bounds on the error probability are derived the multiplicity assignment strategy and the corresponding performance analysis are then generalized to characterize the decoding region of algebraic sdd over a mixed error and bit level erasure channel the bit level decoding region of the proposed multiplicity assignment strategy is shown to be significantly larger than that of conventional berlekamp massey decoding as an application a bit level generalized minimum distance decoding algorithm is proposed the proposed decoding compares favorably with many other reed solomon sdd algorithms over various channels moreover owing to the simplicity of the proposed bit level generalized minimum distance decoding its performance can be tightly bounded using order statistics

two bit bit flipping algorithms for ldpc codes and collective error correction a new class of bit flipping algorithms for low density parity check codes over the binary symmetric channel is proposed compared to the regular parallel or serial bit flipping algorithms the proposed algorithms employ one additional bit at a variable node to represent its strength the introduction of this additional bit allows an increase in the guaranteed error correction capability an additional bit is also employed at a check node to capture information which is beneficial to decoding a framework for failure analysis and selection of two bit bit flipping algorithms is provided the main component of this framework is the re definition of trapping sets which are the most compact tanner graphs that cause decoding failures of an algorithm a recursive procedure to enumerate trapping sets is described this procedure is the basis for selecting a collection of algorithms that work well together it is demonstrated that decoders which employ a properly selected group of the proposed algorithms operating in parallel can offer high speed and low error floor decoding

multiplicative noise removal via a learned dictionary multiplicative noise removal is a challenging image processing problem and most existing methods are based on the maximum a posteriori formulation and the logarithmic transformation of multiplicative denoising problems into additive denoising problems sparse representations of images have shown to be efficient approaches for image recovery following this idea in this paper we propose to learn a dictionary from the logarithmic transformed image and then to use it in a variational model built for noise removal extensive experimental results suggest that in terms of visual quality peak signal to noise ratio and mean absolute deviation error the proposed algorithm outperforms state of the art methods

a computational approach to edge detection this paper describes a computational approach to edge detection the success of the approach depends on the definition of a comprehensive set of goals for the computation of edge points these goals must be precise enough to delimit the desired behavior of the detector while making minimal assumptions about the form of the solution we define detection and localization criteria for a class of edges and present mathematical forms for these criteria as functionals on the operator impulse response a third criterion is then added to ensure that the detector has only one response to a single edge we use the criteria in numerical optimization to derive detectors for several common image features including step edges on specializing the analysis to step edges we find that there is a natural uncertainty principle between detection and localization performance which are the two main goals with this principle we derive a single operator shape which is optimal at any scale the optimal detector has a simple approximate implementation in which edges are marked at maxima in gradient magnitude of a gaussian smoothed image we extend this simple detector using operators of several widths to cope with different signal to noise ratios in the image we present a general method called feature synthesis for the fine to coarse integration of information from operators at different scales finally we show that step edge detector performance improves considerably as the operator point spread function is extended along the edge

analytic estimation of subsample spatial shift using the phases of multidimensional analytic signals in this correspondence a method of analytic subsample spatial shift estimation based on an a priori n d signal model is proposed the estimation uses the linear phases of n analytic signals defined with the multidimensional hilbert transform this estimation proposes i an analytic solution to the n d shift estimation and ii an estimation without processing complex cross correlation function or cross spectra between signals contrary to most phase shift estimators the method provides better performance in estimating subsample shifts than two classical estimators one using the maximum of cross correlation function and the other seeking the zero of the complex correlation function phase two delay estimators using the in phase and quadrature phase components of signals are also compared to our estimator like most estimators using the complex signal phases the estimator proposed herein presents the advantage of unaltered accuracy when low sampled signals are used moreover we show that this method can be applied to motion tracking with ultrasound images thus included in a block based motion estimation method and tested with ultrasound data this estimator provides an analytical solution to the translation estimation problem

a doubly degenerate diffusion model based on the gray level indicator for multiplicative noise removal multiplicative noise removal is a challenging task in image processing inspired by the impressive performance of nonlinear diffusion models in additive noise removal we address this problem in the view of nonlinear diffusion equation theories rather than the traditional variation methods we develop a nonlinear diffusion filter denoising framework which considers not only the information of the gradient of the image but also the information of gray levels of the image furthermore under this framework we propose a doubly degenerate diffusion model for multiplicative noise removal which is analyzed with respect to some of its properties and behavior in denoising process in numerical aspects we present an efficient scheme which uses a stabilization by fast explicit diffusion for the implementation of the multiplicative noise removal model finally the experimental results illustrate effectiveness and efficiency of the proposed model

edge detection in bar code signals corrupted by integrated time varying speckle accurate edge localization is of primary importance in bar code decoding in this paper we investigate statistical properties of edge localization error when a bar code signal is corrupted by additive noise which is a weakly stationary random process we derive a first order approximation for the expected value and standard deviation of the error in terms of the power spectral density psd of the noise this result is used to estimate the edge localization error caused by speckle noise we show that the standard deviation of the error is determined by the intensity distribution of a scanning beam and the positions of neighboring edges we discuss how the error analysis determines the detection rates of a scanning system and how it can be used in the system design analytical examples are provided for upca bar code symbols and a scanning beam with gaussian distribution

unveiling turbo codes some results on parallel concatenated coding schemes a parallel concatenated coding scheme consists of two simple constituent systematic encoders linked by an interleaver the input bits to the first encoder are scrambled by the interleaver before entering the second encoder the codeword of the parallel concatenated code consists of the input bits to the first encoder followed by the parity check bits of both encoders this construction can be generalized to any number of constituent codes parallel concatenated schemes employing two convolutional codes as constituent codes in connection with an iterative decoding algorithm of complexity comparable to that of the constituent codes have been previously shown to yield remarkable coding gains close to theoretical limits they have been named and are known as turbo codes we propose a method to evaluate an upper bound to the bit error probability of a parallel concatenated coding scheme averaged over all interleavers of a given length the analytical bounding technique is then used to shed some light on some crucial questions which have been floating around in the communications community since the proposal of turbo codes

growth of forward masking for sinusoidal and noise maskers as a function of signal delay implications for suppression in noise the first two experiments were designed to determine whether mutual suppression in broadband noise increases in strength with increasing overall level in experiment i masking functions signal threshold versus masker level were measured in forward masking as a function of the delay time of a 10 ms signal both for a broadband noise masker low pass filtered at 8 khz and for sinusoidal maskers at 1 2 and 4 khz in the latter case the signal frequency equaled the masker frequency for short signal delays the masking functions were steeper for the sinusoidal masker than for the noise masker at longer delays the slopes for both masker types decreased and the slopes for the two masker types became more nearly equal in experiment ii we investigated the effect of gating a low level noise cue with the sinusoidal masker at the longer signal delays the masking functions had equal slopes for the broadband noise masker and the sinusoidal masker with cue at short signal delays the masking functions for sinuso

combinatorial bounds for list decoding informally an error correcting code has nice list decodability properties if every hamming ball of large radius has a small number of codewords in it we report linear codes with nontrivial list decodability i e codes of large rate that are nicely list decodable and codes of large distance that are not nicely list decodable specifically on the positive side we show that there exist codes of rate r and block length n that have at most c codewords in every hamming ball of radius h sup 1 1 r 1 c spl middot n this answers the main open question from the work of elias 1957 this result also has consequences for the construction of concatenated codes of good rate that are list decodable from a large fraction of errors improving previous results of guruswami and sudan see ieee trans inform theory vol 45 p 1757 67 sept 1999 and proc 32nd acm symp theory of computing stoc portland or p 181 190 may 2000 in this vein specifically for every spl epsi 0 we present a polynomial time constructible asymptotically good family of binary codes of rate spl omega spl epsi sup 4 that can be list decoded in polynomial time from up to a fraction 1 2 spl epsi of errors using lists of size o spl epsi sup 2 on the negative side we show that for every spl delta and c there exists spl tau 0 and an infinite family of linear codes c sub i sub i such that if n sub i denotes the block length of c sub i then c sub i has minimum distance at least spl delta spl middot n sub i and contains more than c sub 1 spl middot n sub i sup c codewords in some hamming ball of radius spl tau spl middot n sub i while this result is still far from known bounds on the list decodability of linear codes it is the first to bound the radius for list decodability by a polynomial sized list away from the minimum distance of the code

modulation spectra of natural sounds and ethological theories of auditory processing the modulation statistics of natural sound ensembles were analyzed by calculating the probability distributions of the amplitude envelope of the sounds and their time frequency correlations given by the modulation spectra these modulation spectra were obtained by calculating the two dimensional fourier transform of the autocorrelation matrix of the sound stimulus in its spectrographic representation since temporal bandwidth and spectral bandwidth are conjugate variables it is shown that the joint modulation spectrum of sound occupies a restricted space sounds cannot have rapid temporal and spectral modulations simultaneously within this restricted space it is shown that natural sounds have a characteristic signature natural sounds in general are low passed showing most of their modulation energy for low temporal and spectral modulations animal vocalizations and human speech are further characterized by the fact that most of the spectral modulation power is found only for low temporal modulation similarly the distribution of the amplitude envelopes also exhibits characteristic shapes for natural sounds reflecting the high probability of epochs with no sound systematic differences across frequencies and a relatively uniform distribution for the log of the amplitudes for vocalizations it is postulated that the auditory system as well as engineering applications may exploit these statistical properties to obtain an efficient representation of behaviorally relevant sounds to test such a hypothesis we show how to create synthetic sounds with first and second order envelope statistics identical to those found in natural sounds

automatic active model initialization via poisson inverse gradient active models have been widely used in image processing applications a crucial stage that affects the ultimate active model performance is initialization this paper proposes a novel automatic initialization approach for parametric active models in both 2 d and 3 d the pig initialization method exploits a novel technique that essentially estimates the external energy field from the external force field and determines the most likely initial segmentation examples and comparisons with two state of the art automatic initialization methods are presented to illustrate the advantages of this innovation including the ability to choose the number of active models deployed rapid convergence accommodation of broken edges superior noise robustness and segmentation accuracy

on the smallest absorbing sets of ldpc codes from finite planes absorbing sets a class of combinatorial structures of the tanner graph representation of a low density parity check ldpc code are known to influence the performance of the code under message passing iterative decoding in this paper we study the smallest absorbing sets of ldpc codes constructed from projective planes and euclidean planes the lower bounds on the parameters of smallest absorbing sets given by dolecek are proven to be tight for these two families of ldpc codes we also analyze the combinatorial properties of the smallest absorbing sets and give conditions necessary and sufficient for a set of bit nodes in the tanner graph to be a smallest absorbing set for ldpc codes from projective planes we further give a condition necessary and sufficient for a smallest absorbing set to be a fully absorbing set in addition we show that these smallest absorbing sets are asymptotically not stable which may explain to some extent the good performance as well as the low error floor expectation of these two families of ldpc codes

an average weight distance enumerator for binary expansions of reed solomon codes an average hamming weight enumerator is derived for the codewords at each hamming distance from a received pattern in the set of all possible binary expansions of a reed solomon code since these codes may be decoded by list decoders such as those studied by sudan 1997 the enumerator can be used to estimate the average number of codewords in the list returned by such a decoder

reduced complexity iterative decoding of low density parity check codes based on belief propagation two simplified versions of the belief propagation algorithm for fast iterative decoding of low density parity check codes on the additive white gaussian noise channel are proposed both versions are implemented with real additions only which greatly simplifies the decoding complexity of belief propagation in which products of probabilities have to be computed also these two algorithms do not require any knowledge about the channel characteristics both algorithms yield a good performance complexity trade off and can be efficiently implemented in software as well as in hardware with possibly quantized received values

nonlinear multiscale wavelet diffusion for speckle suppression and edge enhancement in ultrasound images this paper introduces a novel nonlinear multiscale wavelet diffusion method for ultrasound speckle suppression and edge enhancement this method is designed to utilize the favorable denoising properties of two frequently used techniques the sparsity and multiresolution properties of the wavelet and the iterative edge enhancement feature of nonlinear diffusion with fully exploited knowledge of speckle image models the edges of images are detected using normalized wavelet modulus relying on this feature both the envelope detected speckle image and the log compressed ultrasonic image can be directly processed by the algorithm without need for additional preprocessing speckle is suppressed by employing the iterative multiscale diffusion on the wavelet coefficients with a tuning diffusion threshold strategy the proposed method can improve the image quality for both visualization and auto segmentation applications we validate our method using synthetic speckle images and real ultrasonic images performance improvement over other despeckling filters is quantified in terms of noise suppression and edge preservation indices

locally monotonic diffusion anisotropic diffusion affords an efficient adaptive signal smoothing technique that can be used for signal enhancement signal segmentation and signal scale space creation this paper introduces a novel partial differential equation pde based diffusion method for generating locally monotonic signals unlike previous diffusion techniques that diverge or converge to trivial signals locally monotonic lomo diffusion converges rapidly to well defined lomo signals of the desired degree the property of local monotonicity allows both slow and rapid signal transitions ramp and step edges while excluding outliers due to noise in contrast with other diffusion methods lomo diffusion does not require an additional regularization step to process a noisy signal and uses no ad hoc thresholds or parameters in the paper we develop the lomo diffusion technique and provide several salient properties including stability and a characterization of the root signals the convergence of the algorithm is well behaved nonoscillatory and is independent of the signal length in contrast with the median filter a special case of lomo diffusion is identical to the optimal solution achieved via regression experimental results validate the claim that lomo diffusion can produce denoised lomo signals with low error using less computation than the median order statistic approach

active contour external force using vector field convolution for image segmentation snakes or active contours have been widely used in image processing applications typical roadblocks to consistent performance include limited capture range noise sensitivity and poor convergence to concavities this paper proposes a new external force for active contours called vector field convolution vfc to address these problems vfc is calculated by convolving the edge map generated from the image with the user defined vector field kernel we propose two structures for the magnitude function of the vector field kernel and we provide an analytical method to estimate the parameter of the magnitude function mixed vfc is introduced to alleviate the possible leakage problem caused by choosing inappropriate parameters we also demonstrate that the standard external force and the gradient vector flow gvf external force are special cases of vfc in certain scenarios examples and comparisons with gvf are presented in this paper to show the advantages of this innovation including superior noise robustness reduced computational cost and the flexibility of tailoring the force field

basilar membrane nonlinearity and loudness loudness matching functions for tones for persons with one shifted threshold ear hearing loss and noise shifted thresholds and one ear within normal limits were used to derive the presumed basilar membrane bm input output i o function in a normal ear the comparison was made by assuming that the bm i o function for the ear with the cochlear threshold shift has a slope of one a linearized cochlea the function for the normal ear was derived from the loudness matching function based on this assumption comparisons were made for archival basilar membrane data m a ruggero n c rich a recio s s narayan and l robles j acoust soc am 101 2151 2163 1997 for chinchilla and archival loudness matches for long duration tones for persons with various degrees of cochlear hearing loss f miskolczy fodor j acoust soc am 32 486 492 1960 comparisons were made also between bm i o functions and ones derived from loudness matches for persons with unilateral hearing loss simulated by broa

ultrasound image restoration based on a learned dictionary and a higher order mrf abstract the restoration of images degraded by blur and multiplicative noise is a critical preprocessing step in medical ultrasound images which exhibit clinical diagnostic features of interest this paper proposes a novel non smooth non convex variational model for ultrasound images denoising and deblurring motivated by the successes of sparse representation of images and foe based approaches dictionaries are well adapted to textures and extended to arbitrary image sizes by defining a global image prior while foe image prior explicitly characterizes the statistics properties of natural image following these ideas the new model is composed of the data fidelity term the sparse and redundant representations via learned dictionaries and the foe image prior model the ipiano algorithm can efficiently deal with this optimization problem the new proposed model is applied to several simulated images and real ultrasound images the experimental results of denoising and deblurring show that proposed method gives a better visual effect by efficiently removing noise and preserving details well compared with two state of the art methods

iterative list decoding of some ldpc codes we present an iterative list decoding algorithm for low density parity check ldpc codes in particular we apply this decoder to a class of ldpc codes from finite geometries and show that the 73 45 10 projective geometry code can be maximum likelihood ml decoded with low complexity moreover the list decoding approach enables us to give a theoretical analysis of the performance we also consider list bit flipping bf decoding of longer ldpc codes

two bit flipping decoding algorithms for low density parity check codes in this letter a low complexity decoding algorithm for binary linear block codes is applied to low density paritycheck ldpc codes and improvements are described namely an extension to soft decision decoding and a loop detection mechanism for soft decoding only one real valued addition per code symbol is needed while the remaining operations are only binary as in the hard decision case the decoding performance is considerably increased by the loop detection simulation results are used to compare the performance with other known decoding strategies for ldpc codes with the result that the presented algorithms offer excellent performances at smaller complexity

iterative soft input soft output decoding of reed solomon codes by adapting the parity check matrix an iterative algorithm is presented for soft input soft output siso decoding of reed solomon rs codes the proposed iterative algorithm uses the sum product algorithm spa in conjunction with a binary parity check matrix of the rs code the novelty is in reducing a submatrix of the binary parity check matrix that corresponds to less reliable bits to a sparse nature before the spa is applied at each iteration the proposed algorithm can be geometrically interpreted as a two stage gradient descent with an adaptive potential function this adaptive procedure is crucial to the convergence behavior of the gradient descent algorithm and therefore significantly improves the performance simulation results show that the proposed decoding algorithm and its variations provide significant gain over hard decision decoding hdd and compare favorably with other popular soft decision decoding methods

a decoding algorithm for finite geometry ldpc codes in this paper we develop a new low complexity algorithm to decode low density parity check ldpc codes the developments are oriented specifically toward low cost yet effective decoding of high rate finite geometry fg ldpc codes the decoding procedure updates iteratively the hard decision received vector in search of a valid codeword in the vector space only one bit is changed in each iteration and the bit selection criterion combines the number of failed checks and the reliability of the received bits prior knowledge of the signal amplitude and noise power is not required an optional mechanism to avoid infinite loops in the search is also proposed our studies show that the algorithm achieves an appealing tradeoff between performance and complexity for fg ldpc codes

on the estimation of the coefficient of variation for anisotropic diffusion speckle filtering in this paper we focus on the problem of speckle removal by means of anisotropic diffusion and specifically on the importance of the correct estimation of the statistics involved first we derive an anisotropic diffusion filter that does not depend on a linear approximation of the speckle model assumed which is the case of a previously reported filter namely srad then we focus on the problem of estimation of the coefficient of variation of both signal and noise and of noise itself our experiments indicate that neighborhoods used for parameter estimation do not need to coincide with those used in the diffusion equations then we show that as long as the estimates are good enough the filter proposed here and the srad perform fairly closely a fact that emphasizes the importance of the correct estimation of the coefficients of variation

nonlocal means based speckle filtering for ultrasound images in image processing restoration is expected to improve the qualitative inspection of the image and the performance of quantitative image analysis techniques in this paper an adaptation of the nonlocal nl means filter is proposed for speckle reduction in ultrasound us images originally developed for additive white gaussian noise we propose to use a bayesian framework to derive a nl means filter adapted to a relevant ultrasound noise model quantitative results on synthetic data show the performances of the proposed method compared to well established and state of the art methods results on real images demonstrate that the proposed method is able to preserve accurately edges and structural details of the image

effects of spectral smearing and temporal fine structure degradation on speech masking release this study assessed the effects of spectral smearing and temporal fine structure tfs degradation on masking release mr the improvement in speech identification in amplitude modulated compared to steady noise observed for normal hearing listeners syllables and noise stimuli were processed using either a spectral smearing algorithm or a tone excited vocoder the two processing schemes simulated broadening of the auditory filters by factors of 2 and 4 simulations of the early stages of auditory processing showed that the two schemes produced comparable excitation patterns however fundamental frequency f0 information conveyed by tfs was degraded more severely by the vocoder than by the spectral smearing algorithm both schemes reduced mr but for each amount of spectral smearing the vocoder produced a greater reduction in mr than the spectral smearing algorithm consistent with the effects of each scheme on f0 representation moreover the effects of spectral smearing on mr produced by the two schemes were different for manner and voicing finally mr data for listeners with moderate hearing loss were well matched by mr data obtained for normal hearing listeners with vocoded stimuli suggesting that impaired frequency selectivity alone may not be sufficient to account for the reduced mr observed for hearing impaired listeners