Daniel Kekrt

Image quality and QoE in multimedia systems

The image and video sensing and processing systems are of high importance nowadays. The crucial parameter is image quality as a part of QoS or more recently QoE (Quality of Experience) as a subjective impact (perception). This invited paper deals with various qualitative aspects in imaging systems. The first part is devoted to the modeling of HVS and image quality evaluation. A model for prediction of perceived quality of degraded images is presented. This model is optimized while incorporating visual attention coordinates. In the following parts four different examples of qualitative impacts (distortions and artifacts) of image post-processing are listed and shown. The first one is the image enhancement, second one image restoration by iterative detectors based on the maximum a posteriori probability criterion, third one image interpolation and finally fourth one image compression and transmission.

The iterative detection network suppression of defocusing and thermal noise in black and white pictures shot by a camera with CCD/CMOS sensor

The paper deals with elimination of defocusing and thermal noise out of black & white pictures captured by a CCD/CMOS camera with imperfectly adjusted lens. For purposes of image recovery we can use the MAP criterion based iterative detection network (IDN) containing a number of mutually concatenated functional blocks so-called soft inversions (SISOs). This cellular structure makes IDN suboptimal but also numerically very simple and practically applicable in contrast to an unviable optimal (single-stage) MAP detector. Firstly we focus closer on SISO entities and consequently on the creation of entire IDN, specifically the so-called distributed IDN marginalizing at the symbol level. In the end, image reconstruction example will be presented (using this type of IDN) along with its performance characteristics (BER curves) for various levels of defocus.

Aspects of image quality enhancement in security technology

During last several years we have studied selected techniques for quality enhancement of security images. The first part of paper demonstrates selected results of image enhancement oriented to the improvement of identification threshold. We have tested the impact of image sharpening algorithms on the display readability in presence of noise. The trade-off between the edge-enhancing and noise treatment is discussed and experimental results are presented.

Restoration of dichromatic images gained from CCD/CMOS camera by iterative detection networks with fragmented marginalization at the symbol block level

Image capturing by CCD/CMOS cameras is encumbered with two fundamental perturbing influences. Time invariant blurring (image convolution with fixed kernel) and time variant noises. Both of these influences can be successfully eliminated by the iterative detection networks (IDNs), that effectively and suboptimally (iteratively) solve 2D MAP criterion through the image decomposition to the small areas. Preferably to the individual pixel level, if this allows the noise distribution (statistically independent noise). Nevertheless, this task is so extremely numerically exacting and therefore the contemporary IDNs are limited only for restorations of dichromatic images. The IDNs are composed of certain, as simple as possible, statistical devices (SISO modules) and can be separated into two basic groups with variable topology (exactly matched to the blurring kernel) and with fixed topology, same for all possible kernels. The paper deals with second group of IDNs, concretely with IDNs whose SISO modules are concatenated in three directions (horizontal, vertical and diagonal). Advantages of such ordering rests in the application flexibility (can be comfortable applied to many irregular cores) and also in the low exigencies to number of memory devices it the IDN. The mentioned IDN type will be implemented in the two different variants suppressing defocusing in the lens of CCD/CMOS sensing system and will be verified in the sphere of a dichromatic 2D barcode detection.

The iterative detection network based recovery of black & white pictures shot by camera (implementation and complexity reduction issue)

The paper deals with a defocusing and Poisson (shot) noise elimination out of black & white pictures captured by a CCD (CMOS) camera with imperfectly adjusted lens. For purposes of this image recovery we can use the MAP criterion based iterative detection network (IDN) containing a number of mutually concatenated elementary function blocks so-called soft inversions (SISOs). This cellular structure makes IDN suboptimal but also numerically very simple and practically applicable in contrast to unviable optimal (single-stage) MAP detector. Firstly we focus closer on SISO entities and consequently on the creation of entire IDN. There will be introduced two different forms of reconstruction system (distributed IDN) together with complexity reduction possibilities and example of the image reconstruction by one of them.

The advanced noise model for an IDN based restoration of black and white pictures captured by a camera with CCD/CMOS sensor

The deterministic blurring and noising in pictures captured by a camera with CCD/CMOS sensor can be fairly simulated as the true image transmission through some kind of ISI channel, with specific 2D impulse response (blurring) and consequently through certain random IECS-ML channel (noising). Hence for purposes of image restoration we can use the maximal a posteriori probability (MAP) criterion based iterative detection network (IDN), that is powered by the noise model and contains a number of mutually concatenated functional blocks so-called soft inversions (SISOs). This cellular structure makes an IDN suboptimal but also numerically very simple and practically applicable in contrast to an unviable optimal (single-stage) MAP detector. This paper is dedicated to the detailed description of the comprehensive noise model that controls the IECS-ML channel and that is applied in the IDN front-end, so-called the soft output demodulator (SODEM). There will be introduced three different examples of IDN front-ends for simpler IDNs, designed only for recovery of black and white images.

The iterative detection network based suppression of the thermal noise and blurring due to object moving in black and white pictures shot by a camera with CCD/CMOS sensor

The paper deals with elimination of blurring caused by the object moving and thermal noise in black & white pictures captured by a CCD/CMOS camera. This problem can be also interpreted like image passage through some kind of ISI channel with specific 2D impulse response. Hence for purposes of image recovery we can use the MAP criterion based iterative detection network (IDN) containing a number of mutually concatenated functional blocks so-called soft inversions (SISOs). This cellular structure makes IDN suboptimal but also numerically very simple and practically applicable in contrast to an unviable optimal (single-stage) MAP detector. Firstly we focus closer to parameters determination of the image blurring hypothetical model (misrepresenting ISI channel). Consequently we are going to deal with the SISO entities and the synthesis of entire IDN, specifically the synthesis of so-called distributed IDN marginalizing at the symbol level because this structure presents the best solution for the mentioned issue. At the end, the image reconstruction example will be presented (using this type of IDN).

Implementation of Different Variants of Table-Based Frequency Synthesizers with Quadrature Output in VHDL

This article describes the modelling and implementation of two different variants of direct frequency synthesizer, and evaluation of the performance of the finished design, in terms of memory and speed efficiency. The frequency synthesizer requirement comes from our complex radio transmission system design. The research activity has been focused on finding an optimal balance between simplicity, speed and memory consumption. The modelling was done in MATLAB environment in floating-point and fixed-point arithmetic, and the actual design was implemented and synthesized using the Xilinx ISE suite. The output has been connected to our customized radio front-end built on the Texas Instruments TRF2443 chip. The front-end output signal has been captured and compared with simulation results.