Hardware-assisted feature analysis and visualization of procedurally encoded multifield volumetric data.
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Content-based adaptive spatio-temporal methods for MPEG repair.
Block loss and propagation error due to cell loss or missing packet information during the transmission over lossy networks can cause severe degradation of block and predictive-based video coding. Herein, new fast spatial and temporal methods are presented for block loss recovery. In the spatial algorithm, missing block recovery and edge extention are performed by pixel replacement based on range constraints imposed by surrounding neighborhood edge information and structure. In the temporal algorithm, an adaptive temporal correlation method is proposed for motion vector (MV) recovery. Parameters for the temporal correlation measurement are adaptively changed in accordance to surrounding edge information of a missing macroblock (MB). The temporal technique utilizes pixels in the reference frame as well as surrounding pixels of the lost block. Spatial motion compensation is applied after MV recovery when the reference frame does not have sufficient information for lost MB restoration. Simulations demonstrate that the proposed algorithms recover image information reliably using both spatial and temporal restoration. We compare the proposed algorithm with other procedures with consistently favorable results.
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Design and statistical analysis of a hash-aided image watermarking system.
This paper develops a joint hashing/watermarking scheme in which a short hash of the host signal is available to a detector. Potential applications include content tracking on public networks and forensic identification. The host data into which the watermark is embedded are selected from a secret subset of the full-frame discrete cosine transform of an image, and the watermark is inserted through multiplicative embedding. The hash is a binary version of selected original image coefficients. We propose a maximum likelihood watermark detector based on a statistical image model. The availability of a hash as side information to the detector modifies the posterior distribution of the marked coefficients. We derive Chernoff bounds on the receiver operating characteristic performance of the detector. We show that host-signal interference can be rejected if the hash function is suitably designed. The relative difficulty of an eavesdropper's detection problem is also determined; the eavesdropper does not know the secret key used. Monte Carlo simulations are performed using photographic test images. Finally, various attacks on the watermarked image are introduced to study the robustness of the derived detectors. The joint hashing/watermarking scheme outperforms the traditional "hashless" watermarking technique.
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A multiple-substream unequal error-protection and error-concealment algorithm for SPIHT-coded video bitstreams.
This paper presents a coordinated multiple-substream unequal error-protection and error-concealment algorithm for SPIHT-coded bitstreams transmitted over lossy channels. In the proposed scheme, we divide the video sequence corresponding to a group of pictures into two subsequences and independently encode each subsequence using a three-dimensional SPIHT algorithm. We use two different partitioning schemes to generate the substreams, each of which offers some advantages under the appropriate channel condition. Each substream is protected by an FEC-based unequal error-protection algorithm, which assigns unequal forward error correction codes to each bit plane. Any information that is lost during the transmission for any substream is estimated at the receiver by using the correlation between the substreams and the smoothness of the video signal. Simulation results show that the proposed multiple-substream UEP algorithm is simple, fast, and robust in hostile network conditions, and that the proposed error-concealment algorithm can achieve 2-3-dB PSNR gain over the case when error concealment is not used at high packet-loss rates.
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JPEG2000-coded image error concealment exploiting convex sets projections.
Transmission errors in JPEG2000 can be grouped into three main classes, depending on the affected area: LL, high frequencies at the lower decomposition levels, and high frequencies at the higher decomposition levels. The first type of errors are the most annoying but can be concealed exploiting the signal spatial correlation like in a number of techniques proposed in the past; the second are less annoying but more difficult to address; the latter are often imperceptible. In this paper, we address the problem of concealing the second class or errors when high bit-planes are damaged by proposing a new approach based on the theory of projections onto convex sets. Accordingly, the error effects are masked by iteratively applying two procedures: low-pass (LP) filtering in the spatial domain and restoration of the uncorrupted wavelet coefficients in the transform domain. It has been observed that a uniform LP filtering brought to some undesired side effects that negatively compensated the advantages. This problem has been overcome by applying an adaptive solution, which exploits an edge map to choose the optimal filter mask size. Simulation results demonstrated the efficiency of the proposed approach.
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Forensic analysis of nonlinear collusion attacks for multimedia fingerprinting.
Digital fingerprinting is a technology for tracing the distribution of multimedia content and protecting them from unauthorized redistribution. Unique identification information is embedded into each distributed copy of multimedia signal and serves as a digital fingerprint. Collusion attack is a cost-effective attack against digital fingerprinting, where colluders combine several copies with the same content but different fingerprints to remove or attenuate the original fingerprints. In this paper, we investigate the average collusion attack and several basic nonlinear collusions on independent Gaussian fingerprints, and study their effectiveness and the impact on the perceptual quality. With unbounded Gaussian fingerprints, perceivable distortion may exist in the fingerprinted copies as well as the copies after the collusion attacks. In order to remove this perceptual distortion, we introduce bounded Gaussian-like fingerprints and study their performance under collusion attacks. We also study several commonly used detection statistics and analyze their performance under collusion attacks. We further propose a preprocessing technique of the extracted fingerprints specifically for collusion scenarios to improve the detection performance.
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Anti-collusion forensics of multimedia fingerprinting using orthogonal modulation.
Digital fingerprinting is a method for protecting digital data in which fingerprints that are embedded in multimedia are capable of identifying unauthorized use of digital content. A powerful attack that can be employed to reduce this tracing capability is collusion, where several users combine their copies of the same content to attenuate/remove the original fingerprints. In this paper, we study the collusion resistance of a fingerprinting system employing Gaussian distributed fingerprints and orthogonal modulation. We introduce the maximum detector and the thresholding detector for colluder identification. We then analyze the collusion resistance of a system to the averaging collusion attack for the performance criteria represented by the probability of a false negative and the probability of a false positive. Lower and upper bounds for the maximum number of colluders K(max) are derived. We then show that the detectors are robust to different collusion attacks. We further study different sets of performance criteria, and our results indicate that attacks based on a few dozen independent copies can confound such a fingerprinting system. We also propose a likelihood-based approach to estimate the number of colluders. Finally, we demonstrate the performance for detecting colluders through experiments using real images.
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Inverse halftoning algorithm using edge-based lookup table approach.
The inverse halftoning algorithm is used to reconstruct a gray image from an input halftone image. Based on the recently published lookup table (LUT) technique, this paper presents a novel edge-based LUT method for inverse halftoning which improves the quality of the reconstructed gray image. The proposed method first uses the LUT-based inverse halftoning method as a preprocessing step to transform the given halftone image to a base gray image, and then the edges are extracted and classified from the base gray image. According to these classified edges, a novel edge-based LUT is built up to reconstruct the gray image. Based on a set of 30 real training images with both low-and high-frequency contents, experimental results demonstrated that the proposed method achieves a better image quality when compared to the currently published two methods, by Chang et al. and Meşe and Vaidyanathan.
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JBEAM: multiscale curve coding via beamlets.
A multiscale coder for curves and boundaries is presented. It utilizes a multiscale structure--beamlets--that is designed primarily for linear and curvilinear features. The coder is composed of three main components: 1) a rate-distortion optimized beamlet-based representation, 2) a tree-based coding from a beamlet representation to a symbol stream, and 3) an entropy coder. This coder is named "JBEAM." Taking advantage of its multiscale property, we utilized tree-based coding to make it progressive. The derived coder has a low order of computational complexity. Simulations demonstrate an advantage over the state-of-the-art industrial standard: JBIG 2. A software package, which includes an implementation of JBEAM, is made available. Variations and potential improvements of this method will be discussed. This work may inspire more activities in this line of research, improving curve coding.
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Optimized transmission of JPEG2000 streams over wireless channels.
The transmission of JPEG2000 images over wireless channels is examined using reorganization of the compressed images into error-resilient, product-coded streams. The product-code consists of Turbo-codes and Reed-Solomon codes which are optimized using an iterative process. The generation of the stream to be transmitted is performed directly using compressed JPEG2000 streams. The resulting scheme is tested for the transmission of compressed JPEG2000 images over wireless channels and is shown to outperform other algorithms which were recently proposed for the wireless transmission of images.
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Lossless watermarking for image authentication: a new framework and an implementation.
We present a novel framework for lossless (invertible) authentication watermarking, which enables zero-distortion reconstruction of the un-watermarked images upon verification. As opposed to earlier lossless authentication methods that required reconstruction of the original image prior to validation, the new framework allows validation of the watermarked images before recovery of the original image. This reduces computational requirements in situations when either the verification step fails or the zero-distortion reconstruction is not needed. For verified images, integrity of the reconstructed image is ensured by the uniqueness of the reconstruction procedure. The framework also enables public(-key) authentication without granting access to the perfect original and allows for efficient tamper localization. Effectiveness of the framework is demonstrated by implementing the framework using hierarchical image authentication along with lossless generalized-least significant bit data embedding.
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High-capacity data hiding in halftone images using minimal-error bit searching and least-mean square filter.
In this paper, a high-capacity data hiding is proposed for embedding a large amount of information into halftone images. The embedded watermark can be distributed into several error-diffused images with the proposed minimal-error bit-searching technique (MEBS). The method can also be generalized to self-decoding mode with dot diffusion or color halftone images. From the experiments, the embedded capacity from 33% up to 50% and good quality results are achieved. Furthermore, the proposed MEBS method is also extended for robust watermarking against the degradation from printing-and-scanning and several kinds of distortions. Finally, a least-mean square-based halftoning is developed to produce an edge-enhanced halftone image, and the technique also cooperates with MEBS for all the applications described above, including high-capacity data hiding with secret sharing or self-decoding mode, as well as robust watermarking. The results prove much sharper than the error diffusion or dot diffusion methods.
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Product code optimization for determinate state LDPC decoding in robust image transmission.
We propose a novel scheme for error-resilient image transmission. The proposed scheme employs a product coder consisting of low-density parity check (LDPC) codes and Reed-Solomon codes in order to deal effectively with bit errors. The efficiency of the proposed scheme is based on the exploitation of determinate symbols in Tanner graph decoding of LDPC codes and a novel product code optimization technique based on error estimation. Experimental evaluation demonstrates the superiority of the proposed system in comparison to recent state-of-the-art techniques for image transmission.
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Distance-preserving projection of high-dimensional data for nonlinear dimensionality reduction.
A distance-preserving method is presented to map high-dimensional data sequentially to low-dimensional space. It preserves exact distances of each data point to its nearest neighbor and to some other near neighbors. Intrinsic dimensionality of data is estimated by examining the preservation of interpoint distances. The method has no user-selectable parameter. It can successfully project data when the data points are spread among multiple clusters. Results of experiments show its usefulness in projecting high-dimensional data.
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Feature subset selection and ranking for data dimensionality reduction.
A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature selection and ranking. In the new algorithm, features are selected in a stepwise way, one at a time, by estimating the capability of each specified candidate feature subset to represent the overall features in the measurement space. A squared correlation function is employed as the criterion to measure the dependency between features and this makes the new algorithm easy to implement. The forward orthogonalization strategy, which combines good effectiveness with high efficiency, enables the new algorithm to produce efficient feature subsets with a clear physical interpretation.
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A vertical-energy-thresholding procedure for data reduction with multiple complex curves.
Due to the development of sensing and computer technology, measurements of many process variables are available in current manufacturing processes. It is very challenging, however, to process a large amount of information in a limited time in order to make decisions about the health of the processes and products. This paper develops a "preprocessing" procedure for multiple sets of complicated functional data in order to reduce the data size for supporting timely decision analyses. The data type studied has been used for fault detection, root-cause analysis, and quality improvement in such engineering applications as automobile and semiconductor manufacturing and nanomachining processes. The proposed vertical-energy-thresholding (VET) procedure balances the reconstruction error against data-reduction efficiency so that it is effective in capturing key patterns in the multiple data signals. The selected wavelet coefficients are treated as the "reduced-size" data in subsequent analyses for decision making. This enhances the ability of the existing statistical and machine-learning procedures to handle high-dimensional functional data. A few real-life examples demonstrate the effectiveness of our proposed procedure compared to several ad hoc techniques extended from single-curve-based data modeling and denoising procedures.
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Emergency peripartum hysterectomy in a tertiary obstetric center: 8-year evaluation.
OBJECTIVE: The aim of the study was to present the incidence, indications, and operative morbidity and mortality in pregnant women undergoing emergency peripartum hysterectomy (EPH) at a tertiary obstetric institution. METHODS: In this retrospective clinical study, performed during the period 1995-2003, 17 EPH procedures were recorded in a total of 21,659 deliveries carried out at Department of Gynecology and Obstetrics, Osijek Clinical Hospital in Osijek, Croatia. Data on the incidence of EPH in total number of deliveries, rate of EPH in vaginal delivery and cesarean section, indications for EPH, and maternal and fetal/early neonatal morbidity and mortality were derived from operative protocols and medical records of hospitalized patients. RESULTS: During the 8-year study period, the incidence of EPH in total number of deliveries was 0.078%. Out of 17 EPH procedures, 5 (29.41%) were performed after vaginal delivery and 12 (70.59%) during cesarean section, elective in five and urgent in seven cases. The indications for EPH included severe peripartum hemorrhage with placenta previa in four, placenta previa percreta in four, various forms of invasive malplacentation (placenta accreta, increta, percreta) in five, uterine rupture in two cases, and atony along with massive retroperitoneal hematoma due to rupture of periuterine vascular bundle during cesarean section in one multipara. EPH was carried out in 12 multipara and five primipara. Lesions of urinary bladder occurred in three cases and were managed by suture. Twelve patients received blood transfusion, whereas development of hemorrhagic shock necessitated transfer to Intensive Care Unit in three patients. No late complications or maternal mortality were recorded. Sixteen total hysterectomies and one supracervical hysterectomy were performed. One case of intrauterine fetal death was caused by total abruptio placenta and uterine rupture during the patient's transport from a primary obstetric institution. CONCLUSION: Invasive malplacentation is a major isolated risk factor for EPH, as shown in the present study. Other risk factors for EPH are massive hemorrhage because placenta previa, uterine atony and uterine rupture associated with multiparity, and previous cesarean section. A great proportion of EPH procedures can be prevented by the introduction of compressive operative methods such as B-Lynch suture in the obstetric algorithms, which will certainly favorably reflect in future fertility and genital health of the female population.
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The effects of digital noise reduction on the acceptance of background noise.
Modern hearing aids commonly employ digital noise reduction (DNR) algorithms. The potential benefit of these algorithms is to provide improved speech understanding in noise or, at the least, to provide relaxed listening or increased ease of listening. In this study, 22 adults were fitted with 16-channel wide-dynamic-range compression hearing aids containing DNR processing. The DNR includes both modulation-based and Wiener-filter-type algorithms working simultaneously. Both speech intelligibility and acceptable noise level (ANL) were assessed using the Hearing in Noise Test (HINT) with DNR on and DNR off. The ANL was also assessed without hearing aids. The results showed a significant mean improvement for the ANL (4.2 dB) for the DNR-on condition when compared to DNR-off condition. Moreover, there was a significant correlation between the magnitude of ANL improvement (relative to DNR on) and the DNR-off ANL. There was no significant mean improvement for the HINT for the DNR on condition, and on an individual basis, the HINT score did not significantly correlate with either aided ANL (DNR on or DNR off). These findings suggest that at least within the constraints of the DNR algorithms and test conditions employed in this study, DNR can significantly improve the clinically measured ANL, which may result in improved ease of listening for speech-in-noise situations.
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