Jakob Dahl Andersen

Optimal context quantization in lossless compression of image data sequences

In image compression context-based entropy coding is commonly used. A critical issue to the performance of context-based image coding is how to resolve the conflict of a desire for large templates to model high-order statistic dependency of the pixels and the problem of context dilution due to insufficient sample statistics of a given input image. We consider the problem of finding the optimal quantizer Q that quantizes the K-dimensional causal context C/sub t/=(X/sub t-t1/,X/sub t-t2/,...,X/sub t-tK/) of a source symbol X/sub t/ into one of a set of conditioning states. The optimality of context quantization is defined to be the minimum static or minimum adaptive code length of given a data set. For a binary source alphabet an optimal context quantizer can be computed exactly by a fast dynamic programming algorithm. Faster approximation solutions are also proposed. In case of m-ary source alphabet a random variable can be decomposed into a sequence of binary decisions, each of which is coded using optimal context quantization designed for the corresponding binary random variable. This optimized coding scheme is applied to digital maps and /spl alpha/-plane sequences. The proposed optimal context quantization technique can also be used to establish a lower bound on the achievable code length, and hence is a useful tool to evaluate the performance of existing heuristic context quantizers.

No-reference analysis of decoded MPEG images for PSNR estimation and post-processing

We propose no-reference analysis and processing of DCT (Discrete Cosine Transform) coded images based on estimation of selected MPEG parameters from the decoded video. The goal is to assess MPEG video quality and perform post-processing without access to neither the original stream nor the code stream. Solutions are presented for MPEG-2 video. A method to estimate the quantization parameters of DCT coded images and MPEG I-frames at the macro-block level is presented. The results of this analysis is used for deblocking and deringing artifact reduction and no-reference PSNR estimation without code stream access. An adaptive deringing method using texture classification is presented. On the test set, the quantization parameters in MPEG-2 I-frames are estimated with an overall accuracy of 99.9% and the PSNR is estimated with an overall average error of 0.3dB. The deringing and deblocking algorithms yield improvements of 0.3dB on the MPEG-2 decoded test sequences.

Lossless image data sequence compression using optimal context quantization

Context based entropy coding often faces the conflict of a desire for large templates and the problem of context dilution. We consider the problem of finding the quantizer Q that quantizes the K-dimensional causal context C/sub i/=(X(i-t/sub 1/), X(i-t/sub 2/), ..., X(i-t/sub K/)) of a source symbol X/sub i/ into one of M conditioning states. A solution giving the minimum adaptive code length for a given data set is presented (when the cost of the context quantizer is neglected). The resulting context quantizers can be used for sequential coding of the sequence X/sub 0/, X/sub 1/, X/sub 2/, .... A coding scheme based on binary decomposition and context quantization for coding the binary decisions is presented and applied to digital maps and /spl alpha/-plane sequences. The optimal context quantization is also used to evaluate existing heuristic context quantizations.

Selection of component codes for turbo coding based on convergence properties

The turbo decoding is a sub-optimal decoding, i.e. it is not a maximum likelihood decoding. It is important to be aware of this fact when the parameters for the scheme are chosen. This goes especially for the selection of component codes, where the selection often has been based solely on the performance at highSnr’s. We will show that it is important to base the choice on the performance at lowSnr’s. i.e. the convergence properties, as well. Further, the study of the performance with different component codes may lead to an understanding of the convergence process in the turbo decoder.RésuméLe turbo décodage est sous optimal car il n’est pas à maximum de vraisemblance. Il est important de tenir compte de ce fait pour choisir les paramètres du schéma de codage. Cela est particulièrement vrai pour le choix des codes élémentaires qui sont souvent sélectionnés en fonction de leur comportement à fort signal à bruit. L’auteur montre qu’il est aussi important de choisir ces codes en tenant compte de leurs performances à faible rapport signal à bruit. De plus, l’étude des performances des turbo codes avec différents codes élémentaires peut conduire à une meilleure compréhension du processus de convergence du turbo décodeur.

Subjective quality of video sequences rendered on LCD with local backlight dimming at different lighting conditions

This paper focuses on the influence of ambient light on the perceived quality of videos displayed on Liquid Crystal Display (LCD) with local backlight dimming. A subjective test assessing the quality of videos with two backlight dimming methods and three lighting conditions, i.e. no light, low light level (5 lux) and higher light level (60 lux) was organized to collect subjective data. Results show that participants prefer the method exploiting local dimming possibilities to the conventional full backlight but that this preference varies depending on the ambient light level. The clear preference for one method at the low light conditions decreases at the high ambient light, confirming that the ambient light significantly attenuates the perception of the leakage defect (light leaking through dark pixels). Results are also highly dependent on the content of the sequence, which can modulate the effect of the ambient light from having an important influence on the quality grades to no influence at all.

Critical lengths of error events in convolutional codes

If the calculation of the critical length is based on the expurgated exponent, the length becomes nonzero for low error probabilities. This result applies to typical long codes, but it may also be useful for modeling error events in specific codes. >

Hardware implementation of MPEG analysis and deblocking for video enhancement

In this work, we develop an architecture to implement a deblocking filter to improve the quality of video decoded from MPEG. The filter is controlled by the quantization scale parameter, which is derived from the decoded stream based on a novel algorithm. The hardware implementation is targeting an FPGA device similar to those currently used in post-processing units of high end flat panel TV sets. The designed filter shows good performance in terms of robust signal-to-noise ratio and its implementation meets the area and frequency constraints.

A configurable FPGA FEC unit for Tb/s optical communication

Decoding of FEC (forward error correction) for optical communication beyond 1 Tb/s is investigated. A configurable single FPGA solution is presented having configurations supporting bit-rates in the range from 40 Gb/s to 1.6 Tb/s. The design allows for trade-offs of bit-rate, footprint, and latency within the resources of the FPGA. A proof-of-concept lab experiment at 40 Gb/s was conducted and pre-FEC — post-FEC performance validated with simulated results.