The purpose of this work is to evaluate how the choice of mother wavelet function affects ultrasound image denoising. The paper presents a detailed analysis of the properties of each wavelet family highlighting their properties and limitations in ultrasound image filtering applications. The study has been carried out using controlled noise-variance ultrasound images simulated by Field II program in order to compare the effectiveness of filtering. Medical image quality for each wavelet function has been evaluated using two different metrics: the classical peak signal-to-noise ratio and the edges preservation in the filtered image. Significant remarks have been found out from the analysis providing valuable information to obtain best image for ultrasound exams. Finally real high-quality ultrasound images have been processed by the proposed method to validate obtained results.

The shore-side electrical power supply to a ship at berth (also known as Cold Ironing –CI) is an important issue to obtain the reduction of ship emissions and to make ports more environmental-friendly. Due to European Commission recommendations the principal European ports are planning to install this technology, especially for harbour areas with high pollution levels. In this context, the municipality of Taranto (Italy) is focusing its attention on new actions aimed at the environmental requalification of port area based on cold ironing. In this paper, the authors gather and analyze the data associated with the berthing operations and resulting emissions to better define suitable actions for emissions reduction and to suggest some possible strategies for bringing down pollutants, in order to reach a wealth based on environmental preservation.

This paper presents a novel parametric thresholding procedure to reduce the effect of speckle noise in ultrasound (US) medical images. The method comprises the use of an adaptive data-driven exponential operator that operates on wavelet coefficients of the US image to suppress undesired effects of disturbances, preserving signal details. The obtained results demonstrate that the proposed denoising method increases the medical image quality and, therefore, it can be a useful tool in medical diagnosis.

Recently, many complex medical exams require correlating the information from magnetic resonance (MR) and computed tomography (CT) images in order to obtain a more accurate diagnostics. This is rather complex when the images under test have very different noise level. In this paper, a technique to compare the quality of the CT and MR images is introduced. The proposed technique is useful to assess the effect of different noise distribution on medical images and to equalize the examinations produced by different imagining technologies in terms of clearness of images and sharpness of contours. The authors, after examining the statistical properties of the noise affecting CT and MR images, analyze its effect on final image quality. Then, a methodology to compare the mean square errors relevant to CT and MR images is proposed. The study was carried out using 148 images obtained from patients under neuropsychological test. The experimental tests have been performed by corrupting the original data with different noise levels.

The main purpose of this work is the assessment of quality performance of medical imaging systems by using objective image quality tests. To this aim, the influence of radiographic parameters has been investigated in order to reduce radiation dose to patients by assuring a good quality of the images.

The aim of this work is to present the new activities planned by the Electric and Electronic Measurements Research Group of Polytechnic of Bari, Department of Electric and Information Engineering, under the strategic project named "Magna Grecia - Rafforzamento Strutturale", funded by the Italian Ministry of Education, University and Research within the National Operating Program Research and Competitiveness 2007-2013. The project aims to cooperate with many Apulia Regional Authorities to build a network for the monitoring of many pollution sources in the State of Taranto, which have already caused and continue to cause a heavy degradation of air, water, soil and electromagnetic spectrum