Objective evaluation of a subjective image quality assessment plays a significant role in the various image processing applications, such as compression, interpolation and noise reduction. The subjective image quality assessment does not only depend on some objective measurable artefacts, but also on image content and kind of distortions. Thus, a multi‐parameter prediction of the objective image quality assessment is proposed in this study. The prediction parameters are found minimising the mean square error related to the known subjective image quality measure (DMOS). This approach includes mostly used image quality metrics (peak signal‐to‐noise ratio, multi‐scale structural similarity image measure, feature similarity image measure, video quality measure) and two‐dimensional image quality metrics (2D IQM). The proposed multi‐parameter prediction has been verified on the test image database (LIVE) for compression, noise and blur distortions with available subjective image quality measures (DMOS). More reliable estimations are obtained using multi‐parameter prediction instead of only one measure. The best results are reached when an image content indicator is combined with the 2D IQM measure separately for different kinds of distortions.

This paper presents lessons learned from the FP7 project E2LP (Embedded Engineering Learning Platform) and describes the post-project activities: continued usage and experiences in laboratory exercises in the Digital System Design course for second-year students at University of Novi Sad. Introduced E2LP platform increased students' interest to the course and influenced increase in the received grades. The paper also gives insight into the application of E2LP with high school students at one workshop which resulted in mostly positive feedback from the participants of the workshop.

The main idea behind this project is to provide a unified platform which will cover a complete process for embedded systems learning. A modular approach is considered for skills practice through supporting individualization in learning. This platform shall facilitate a novel development of universal approach in creative learning environment and knowledge management that encourage use of ICT. New learning model is challenging the education of engineers in embedded systems design through real-time experiments that stimulate curiosity with ultimate goal to support students to understand and construct their personal conceptual knowledge based on experiments. In addition to the technological approach, the use of cognitive theories on how people learn will help students to achieve a stronger and smarter adaptation of the subject. Applied methodology will be evaluated from the scientific point of view in parallel with the implementation in order to feedback results to the R&D.

This paper presents a generic processor for unified computer engineering learning platform. The processor design is part of the first course in design of digital systems at the Department of Computer Engineering and Communications at University of Novi Sad. It is designed and synthesized for an FPGA-based board.

A window design and fast algorithm for the overlapping block transform (OBT) of size N/spl times/L are presented. The presented algorithm for the OBT reduces the calculation complexity to an N/spl times/N transform with a fast algorithm and a simple preprocessing including windowing. A signal-independent window optimization strategy is introduced for image coding application. Results for a first-order Markov model and an image coding experiment show, that the coding gains of the optimized OBTs increase and blocking effects decrease with increasing window length L. A comparison with DCT-coding shows that the OBT, which has a slightly increased realization complexity, provides higher coding gain and a significant blocking effect reduction.>

A common theory of lapped orthogonal transforms (LOTs) and critically sampled filter banks, called L into N coding (LINC), is presented. The theory includes a unified analysis of both coding methods and identity relations between the transform, inverse transform, analysis filter bank, and synthesis filter bank. A design procedure for LINC analysis/synthesis systems, which satisfy the conditions for perfect reconstruction, is developed. The common LINC theory is used to define an ideal LINC system which is used, together with the power spectral density of the input signal, to calculate theoretical bounds for the coding gain. A generalized overlapping block transform (OBT) with time domain aliasing cancellation (TDAC) is used to approximate the ideal LINC. A generalization of the OBT includes multiple block overlap and additional windowing. A recursive design procedure for windows of arbitrary lengths is presented. The coding gain of the generalized OBT is higher than that of the Karhunen-Loeve transform (KLT) and close to the theoretical bounds for LINC. In the case of image coding, the generalized OBT reduces the blocking effects when compared with the DCT.>

The general conditions of exact reconstruction and a recursive design procedure for lapped orthogonal transform (LOT) with arbitrary length of overlapping are presented. It is shown that LOT can be realized with any standard block transform, discrete cosine transform (DCT), for example, and an additional processing. This processing must also satisfy the same conditions for exact reconfigurations and it may be pretransform processing in the time domain or post-transform processing in the transform domain. In a few examples it is shown that the LOT has a higher coding gain and smaller blocking effects then DCT. With the proposed LOT design procedure, two optimizations, the coding gain maximization and the blocking effect minimization, are presented and compared.