ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California / Aerial image collections have experienced exponential growth in size in recent years. These high resolution images are often viewed at a variety of scales. When an image is displayed at reduced scale, maximum quantization step sizes for visually lossless quality become larger. However, previous visually lossless coding algorithms quantize the image with a single set of quantization step sizes, optimized for display at the full resolution level. This implies that if the image is rendered at reduced resolution, there are significant amounts of extraneous information in the codestream. Thus, in this paper, we propose a method which effectively incorporates multiple quantization step sizes, for various display resolutions, into the JPEG2000 framework. If images are browsed from a remote location, this method can significantly reduce bandwidth usage by only transmitting the portion of the codestream required for visually lossless reconstruction at the desired resolution. Experimental results for high resolution color aerial images are presented.

ITC/USA 2009 Conference Proceedings / The Forty-Fifth Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2009 / Riviera Hotel & Convention Center, Las Vegas, Nevada / This paper describes a psychophysical experiment to measure visibility thresholds (VT) for quantization distortion in JPEG2000 and an associated quantization algorithm for visually lossless coding of color aerial images. The visibility thresholds are obtained from a quantization distortion model based on the statistical characteristics of wavelet coefficients and the deadzone quantizer of JPEG2000, and the resulting visibility thresholds are presented for the luminance component (Y) and two chrominance components (Cb and Cr). Using the thresholds, we have achieved visually lossless coding for 24-bit color aerial images at an average bitrate of 4.17 bits/pixels, which is approximately 30% of the bitrate required for numerically lossless coding.

ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / This paper described the details of subjective validation for visually lossless compression of stereoscopic 3 dimensional (3D) images. The subjective testing method employed in this work is adapted from methods used previously for visually lossless compression of 2 dimensional (2D) images. Confidence intervals on the correct response rate obtained from the subjective validation of compressed stereo pairs provide reliable evidence to indicate that the compressed stereo pairs are visually lossless.

ITC/USA 2012 Conference Proceedings / The Forty-Eighth Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2012 / Town and Country Resort & Convention Center, San Diego, California / This paper proposes a method of measuring visibility thresholds for quantization distortion in JPEG2000 for compression of stereoscopic 3D images. The crosstalk effect is carefully considered to ensure that quantization errors in each channel of stereoscopic images are imperceptible to both eyes. A model for visibility thresholds is developed to reduce the daunting number of measurements required for subjective experiments.

A new progressive lossy-to-lossless coding method for arbitrarily-connected triangle mesh models of bivariate functions is proposed. The algorithm employs a novel representation of a mesh dataset called a bivariate-function description (BFD) tree, and codes the tree in an efficient manner. The proposed coder yields a particularly compact description of the mesh connectivity by only coding the constrained edges that are not locally preferred Delaunay (locally PD). Experimental results show our method to be vastly superior to previously-proposed coding frameworks for both lossless and progressive coding performance. For lossless coding performance, the proposed method produces the coded bitstreams that are 27.3% and 68.1% smaller than those generated by the Edgebreaker and Wavemesh methods, respectively. The progressive coding performance is measured in terms of the PSNR of function reconstructions generated from the meshes decoded at intermediate stages. The experimental results show that the function approximations obtained with the proposed approach are vastly superior to those yielded with the image tree (IT) method, the scattered data coding (SDC) method, the average-difference image tree (ADIT) method, and the Wavemesh method with an average improvement of 4.70 dB, 10.06 dB, 2.92 dB, and 10.19 dB in PSNR, respectively. The proposed coding approach can also be combined with a mesh generator to form a highly effective mesh-based image coding system, which is evaluated by comparing to the popular JPEG2000 codec for images that are nearly piecewise smooth. The images are compressed with the mesh-based image coder and the JPEG2000 codec at the fixed compression rates and the quality of the resulting reconstructions are measured in terms of PSNR. The images obtained with our method are shown to have a better quality than those produced by the JPEG2000 codec, with an average improvement of 3.46 dB. / Graduate

A contextual lightweight arithmetic coder is proposed for lossless compression of medical imagery. Context definition uses causal data from previous symbols coded, an inexpensive yet efficient approach. To further reduce the computational cost, a binary arithmetic coder with fixed-length codewords is adopted, thus avoiding the normalization procedure common in most implementations, and the probability of each context is estimated through bitwise operations. Experimental results are provided for several medical images and compared against state-of-the-art coding techniques, yielding on average improvements between nearly 0.1 and 0.2 bps.

Image sizes have increased exponentially in recent years. The resulting high-resolution images are often viewed via remote image browsing. Zooming and panning are desirable features in this context, which result in disparate spatial regions of an image being displayed at a variety of ( spatial) resolutions. When an image is displayed at a reduced resolution, the quantization step sizes needed for visually lossless quality generally increase. This paper investigates the quantization step sizes needed for visually lossless display as a function of resolution, and proposes a method that effectively incorporates the resulting ( multiple) quantization step sizes into a single JPEG 2000 codestream. This codestream is JPEG 2000 Part 1 compliant and allows for visually lossless decoding at all resolutions natively supported by the wavelet transform as well as arbitrary intermediate resolutions, using only a fraction of the full-resolution codestream. When images are browsed remotely using the JPEG 2000 Interactive Protocol ( JPIP), the required bandwidth is significantly reduced, as demonstrated by extensive experimental results.

Ce projet de recherche doctoral vise à proposer solution améliorée du codec de codage d’images LAR (Locally Adaptive Resolution), à la fois d’un point de vue performances de compression et complexité. Plusieurs standards de compression d’images ont été proposés par le passé et mis à profit dans de nombreuses applications multimédia, mais la recherche continue dans ce domaine afin d’offrir de plus grande qualité de codage et/ou de plus faibles complexité de traitements. JPEG fut standardisé il y a vingt ans, et il continue pourtant à être le format de compression le plus utilisé actuellement. Bien qu’avec de meilleures performances de compression, l’utilisation de JPEG 2000 reste limitée due à sa complexité plus importe comparée à JPEG. En 2008, le comité de standardisation JPEG a lancé un appel à proposition appelé AIC (Advanced Image Coding). L’objectif était de pouvoir standardiser de nouvelles technologies allant au-delà des standards existants. Le codec LAR fut alors proposé comme réponse à cet appel. Le système LAR tend à associer une efficacité de compression et une représentation basée contenu. Il supporte le codage avec et sans pertes avec la même structure. Cependant, au début de cette étude, le codec LAR ne mettait pas en oeuvre de techniques d’optimisation débit/distorsions (RDO), ce qui lui fut préjudiciable lors de la phase d’évaluation d’AIC. Ainsi dans ce travail, il s’agit dans un premier temps de caractériser l’impact des principaux paramètres du codec sur l’efficacité de compression, sur la caractérisation des relations existantes entre efficacité de codage, puis de construire des modèles RDO pour la configuration des paramètres afin d’obtenir une efficacité de codage proche de l’optimal. De plus, basée sur ces modèles RDO, une méthode de « contrôle de qualité » est introduite qui permet de coder une image à une cible MSE/PSNR donnée. La précision de la technique proposée, estimée par le rapport entre la variance de l’erreur et la consigne, est d’environ 10%. En supplément, la mesure de qualité subjective est prise en considération et les modèles RDO sont appliqués localement dans l’image et non plus globalement. La qualité perceptuelle est visiblement améliorée, avec un gain significatif mesuré par la métrique de qualité objective SSIM. Avec un double objectif d’efficacité de codage et de basse complexité, un nouveau schéma de codage LAR est également proposé dans le mode sans perte. Dans ce contexte, toutes les étapes de codage sont modifiées pour un meilleur taux de compression final. Un nouveau module de classification est également introduit pour diminuer l’entropie des erreurs de prédiction. Les expérimentations montrent que ce codec sans perte atteint des taux de compression équivalents à ceux de JPEG 2000, tout en économisant 76% du temps de codage et de décodage. / This doctoral research project aims at designing an improved solution of the still image codec called LAR (Locally Adaptive Resolution) for both compression performance and complexity. Several image compression standards have been well proposed and used in the multimedia applications, but the research does not stop the progress for the higher coding quality and/or lower coding consumption. JPEG was standardized twenty years ago, while it is still a widely used compression format today. With a better coding efficiency, the application of the JPEG 2000 is limited by its larger computation cost than the JPEG one. In 2008, the JPEG Committee announced a Call for Advanced Image Coding (AIC). This call aims to standardize potential technologies going beyond existing JPEG standards. The LAR codec was proposed as one response to this call. The LAR framework tends to associate the compression efficiency and the content-based representation. It supports both lossy and lossless coding under the same structure. However, at the beginning of this study, the LAR codec did not implement the rate-distortion-optimization (RDO). This shortage was detrimental for LAR during the AIC evaluation step. Thus, in this work, it is first to characterize the impact of the main parameters of the codec on the compression efficiency, next to construct the RDO models to configure parameters of LAR for achieving optimal or sub-optimal coding efficiencies. Further, based on the RDO models, a “quality constraint” method is introduced to encode the image at a given target MSE/PSNR. The accuracy of the proposed technique, estimated by the ratio between the error variance and the setpoint, is about 10%. Besides, the subjective quality measurement is taken into consideration and the RDO models are locally applied in the image rather than globally. The perceptual quality is improved with a significant gain measured by the objective quality metric SSIM (structural similarity). Aiming at a low complexity and efficient image codec, a new coding scheme is also proposed in lossless mode under the LAR framework. In this context, all the coding steps are changed for a better final compression ratio. A new classification module is also introduced to decrease the entropy of the prediction errors. Experiments show that this lossless codec achieves the equivalent compression ratio to JPEG 2000, while saving 76% of the time consumption in average in encoding and decoding.

Είναι γεγονός ότι το ηλεκτροκαρδιογράφημα είναι ένα πολύ καλά μελετημένο σήμα. Ειδικά τα τελευταία χρόνια, έχει προταθεί ένας μεγάλος αριθμός αλγορίθμων επεξεργασίας, συμπίεσης, αυτόματης διάγνωσης, φιλτραρίσματος, αποθορυβοποίησης και κωδικοποίησης. Σ’ αυτή τη διπλωματική εργασία, προτείνουμε ένα αποδοτικό αλγόριθμο κωδικοποίησης χωρίς απώλειες για δεδομένα από δωδεκακάναλλο ηλεκτροκαρδιογράφημα. Ο κωδικοποιητής υλοποιεί ένα πολυγραμμικό μοντέλο υψηλής απόδοσης, το οποίο είναι «ειδικευμένο στους ασθενείς», ενδοκαναλικής πρόβλεψη και εφαρμόζει το πρότυπο κωδικοποίησης MPEG-4 ALS για διακαναλική πρόβλεψη και κωδικοποίηση. Τα αποτελέσματα του αλγορίθμου συγκρίθηκαν με τεχνικές κωδικοποίησης εντροπίας χωρίς απώλειες και δείχνουν αύξηση της απόδοσης κωδικοποίησης. / The Electrocardiogram (ECG) is one of the most well studied medical signals. A large number of ECG processing algorithms have being proposed over the years covering the areas of ECG noise filtering, automated diagnostic interpretation and coding. In this master thesis, we propose a robust multi-channel ECG encoder architecture, which operates on 12-channel ECG data. The encoder utilizes highly efficient multi-linear patient specific models for inter-channel prediction and the MPEG-4 Audio Lossless Coding (ALS) architecture for intra-channel prediction and coding. The results of the algorithm show improved performance over standard encoding techniques.