Joint Optimization of Low-power DCT Architecture and Effcient Quantization Technique for Embedded Image Compression

International audienceThe Discrete Cosine Transform (DCT)-based image com- pression is widely used in today's communication systems. Signi cant research devoted to this domain has demonstrated that the optical com- pression methods can o er a higher speed but su er from bad image quality and a growing complexity. To meet the challenges of higher im- age quality and high speed processing, in this chapter, we present a joint system for DCT-based image compression by combining a VLSI archi- tecture of the DCT algorithm and an e cient quantization technique. Our approach is, rstly, based on a new granularity method in order to take advantage of the adjacent pixel correlation of the input blocks and to improve the visual quality of the reconstructed image. Second, a new architecture based on the Canonical Signed Digit and a novel Common Subexpression Elimination technique is proposed to replace the constant multipliers. Finally, a recon gurable quantization method is presented to e ectively save the computational complexity. Experimental results obtained with a prototype based on FPGA implementation and com- parisons with existing works corroborate the validity of the proposed optimizations in terms of power reduction, speed increase, silicon area saving and PSNR improvement

Workshop on Verification and Theorem Proving for Continuous Systems (NetCA Workshop 2005)

Oxford, UK, 26 August 200

Signal-to-noise ratio estimation in digital computer simulation of lowpass and bandpass systems with applications to analog and digital communications, volume 3

Techniques are developed to estimate power gain, delay, signal-to-noise ratio, and mean square error in digital computer simulations of lowpass and bandpass systems. The techniques are applied to analog and digital communications. The signal-to-noise ratio estimates are shown to be maximum likelihood estimates in additive white Gaussian noise. The methods are seen to be especially useful for digital communication systems where the mapping from the signal-to-noise ratio to the error probability can be obtained. Simulation results show the techniques developed to be accurate and quite versatile in evaluating the performance of many systems through digital computer simulation

Digit-slicing architectures for real-time digital filters

One of the many important algorithmic techniques in digital signal processing is real-time digital filtering. Modular sliced structures for digital filters have been proposed before, but the nature of implementation has been mainly constrained to non-recursive second order digital filters with positive values of coefficients. The aim of this research project is to extend this modular digit slicing concept to more practical higher order digital filters which are recursive and are of many forms (direct, nondirect, canonic, non-canonic). [Continues.

Wordlength determination algorithms for hardware implementation of linear time invariant systems with prescribed output accuracy

This paper proposes two novel algorithms for optimizing the hardware resources in finite wordlength implementation of linear time invariant systems. The hardware complexity is measured by the exact internal wordlength used for each intermediate data. The first algorithm formulates the design problem as a constrained optimization, from which an analytic closed-form solution of the internal wordlengths subject to a prescribed output accuracy can be determined by the Lagrange multiplier method. The second algorithm is based on a discrete optimization method called the Marginal Analysis method, and it yields the desired wordlengths in integer values. Both approaches are found to be very effective and they are well-suited to large scale systems such as software radio receivers. Design examples show that the proposed algorithms offer better results and a lower design complexity than conventional methods. © 2005 IEEE.published_or_final_versio

Digital Filters and Signal Processing

Digital filters, together with signal processing, are being employed in the new technologies and information systems, and are implemented in different areas and applications. Digital filters and signal processing are used with no costs and they can be adapted to different cases with great flexibility and reliability. This book presents advanced developments in digital filters and signal process methods covering different cases studies. They present the main essence of the subject, with the principal approaches to the most recent mathematical models that are being employed worldwide

Optimization of Planck/LFI on--board data handling

To asses stability against 1/f noise, the Low Frequency Instrument (LFI) onboard the Planck mission will acquire data at a rate much higher than the data rate allowed by its telemetry bandwith of 35.5 kbps. The data are processed by an onboard pipeline, followed onground by a reversing step. This paper illustrates the LFI scientific onboard processing to fit the allowed datarate. This is a lossy process tuned by using a set of 5 parameters Naver, r1, r2, q, O for each of the 44 LFI detectors. The paper quantifies the level of distortion introduced by the onboard processing, EpsilonQ, as a function of these parameters. It describes the method of optimizing the onboard processing chain. The tuning procedure is based on a optimization algorithm applied to unprocessed and uncompressed raw data provided either by simulations, prelaunch tests or data taken from LFI operating in diagnostic mode. All the needed optimization steps are performed by an automated tool, OCA2, which ends with optimized parameters and produces a set of statistical indicators, among them the compression rate Cr and EpsilonQ. For Planck/LFI the requirements are Cr = 2.4 and EpsilonQ <= 10% of the rms of the instrumental white noise. To speedup the process an analytical model is developed that is able to extract most of the relevant information on EpsilonQ and Cr as a function of the signal statistics and the processing parameters. This model will be of interest for the instrument data analysis. The method was applied during ground tests when the instrument was operating in conditions representative of flight. Optimized parameters were obtained and the performance has been verified, the required data rate of 35.5 Kbps has been achieved while keeping EpsilonQ at a level of 3.8% of white noise rms well within the requirements.Comment: 51 pages, 13 fig.s, 3 tables, pdflatex, needs JINST.csl, graphicx, txfonts, rotating; Issue 1.0 10 nov 2009; Sub. to JINST 23Jun09, Accepted 10Nov09, Pub.: 29Dec09; This is a preprint, not the final versio

Design and multiplierless realization of digital synthesis filters for hybrid-filter-bank A/D converters

This paper studies the optimal least squares and minimax design and realization of digital synthesis filters for hybrid-filter-bank analog-to-digltal converters (HFB ADCs) to meet a given spurious-free dynamic range (SFDR). The problem for designing finite-impulse-response synthesis filters is formulated as a second-order cone-programming problem, which is convex and allows linear and quadratic constraints such as peak aliasing error to be incorporated. The fixed coefficients of the designed synthesis filters are efficiently implemented using sum-of-power-of-two (SOPOT) coefficients, while the internal word length used for each intermediate data is minimized using geometric programming. The main sources of error are analyzed, and a new formula of SFDR in terms of these errors is derived. The effects of component variations of analog analysis filters on the HFB ADC are also addressed by means of two new robust HFB ADC design algorithms based on stochastic uncertainty and worst case uncertainty models. Design results show that the proposed approach offers more flexibility and better performance than conventional methods in achieving a given SFDR and that the robust design algorithms are more robust to parameter uncertainties than the nominal design in which the uncertainties are not taken into account. © 2009 IEEE.published_or_final_versio