Projections Onto Convex Sets through Particle Swarm Optimization and its application for remote sensing image restoration

Image restoration attempts to enhance images corrupted by noise and blurring effects. Iterative approaches can better control the restoration algorithm in order to find a compromise of restoring high details in smoothed regions without increasing the noise. Techniques based on Projections Onto Convex Sets (POCS) have been extensively used in the context of image restoration by projecting the solution onto hyperspaces until some convergence criteria be reached. It is expected that an enhanced image can be obtained at the final of an unknown number of projections. The number of convex sets and its combinations allow designing several image restoration algorithms based on POCS. Here, we address two convex sets: Row-Action Projections (RAP) and Limited Amplitude (LA). Although RAP and LA have already been used in image restoration domain, the former has a relaxation parameter (A) that strongly depends on the characteristics of the image that will be restored, i.e., wrong values of A can lead to poorly restoration results. In this paper, we proposed a hybrid Particle Swarm Optimization (PS0)-POCS image restoration algorithm, in which the A value is obtained by PSO to be further used to restore images by POCS approach. Results showed that the proposed PSO-based restoration algorithm outperformed the widely used Wiener and Richardson-Lucy image restoration algorithms. (C) 2010 Elsevier B.V. All rights reserved.

A hybrid image restoration algorithm based on Projections onto Convex Sets and Harmony Search

Image restoration is a research field that attempts to recover a blurred and noisy image. Since it can be modeled as a linear system, we propose in this paper to use the meta-heuristics optimization algorithm Harmony Search (HS) to find out near-optimal solutions in a Projections Onto Convex Sets-based formulation to solve this problem. The experiments using HS and four of its variants have shown that we can obtain near-optimal and faster restored images than other evolutionary optimization approach. © 2013 IEEE.

On the efficiency of an alternative codification for multiobjective service restoration in electric distribution networks

This paper proposes an alternative codification to solve the service restoration in electric power distribution networks using a SPEA2 multiobjective evolutionary algorithm, assuming the minimization of both the load not supplied and the number of switching operations involved in the restoration plan. Constrains as the line, power source and voltage drop limits in order to avoid the activation of protective devices are all included in the proposed algorithm. Experimental results have shown the convenience on considering these new representations in the sense of feasibility maintenance and also in the sense of better approximation to the Pareto set. ©2009 IEEE.

A well-balanced flow equation for noise removal and edge detection

In this paper, an anisotropic nonlinear diffusion equation for image restoration is presented. The model has two terms: the diffusion and the forcing term. The balance between these terms is made in a selective way, in which boundary points and interior points of the objects that make up the image are treated differently. The optimal smoothing time concept, which allows for finding the ideal stop time for the evolution of the partial differential equation is also proposed. Numerical results show the proposed model's high performance.

Estudo de métodos numéricos para eliminação de ruídos em imagens digitais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Restauração de imagens utilizando projeções em conjuntos convexos e algoritmos evolucionistas

Pós-graduação em Ciência da Computação - IBILCE

Three-Dimensional Semiautomatic Road Extraction From a High-Resolution Aerial Image by Dynamic-Programming Optimization in the Object Space

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of phantom for radiographic image optimization of standard patient in the lateral view of chest and skull examination

We present the construction of a homogeneous phantom to be used in simulating the scattering and absorption of X-rays by a standard patient chest and skull when irradiated laterally. This phantom consisted of Incite and aluminium plates with their thickness determined by a tomographic exploratory method applied to the anthropomorphic phantom. Using this phantom, an optimized radiographic technique was established for chest and skull of standard sized patient in lateral view. Images generated with this optimized technique demonstrated improved image quality and reduced radiation doses. (c) 2006 Elsevier Ltd. All rights reserved.

Phantom development for radiographic image optimization of chest, skull and pelvis examination for nonstandard patient

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of aluminum-copper alloy filtration on photon spectra, air kerma rate and image contrast

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Global optimization for the ℋ∞-norm model reduction problem

A branch and bound algorithm is proposed to solve the [image omitted]-norm model reduction problem for continuous and discrete-time linear systems, with convergence to the global optimum in a finite time. The lower and upper bounds in the optimization procedure are described by linear matrix inequalities (LMI). Also proposed are two methods with which to reduce the convergence time of the branch and bound algorithm: the first one uses the Hankel singular values as a sufficient condition to stop the algorithm, providing to the method a fast convergence to the global optimum. The second one assumes that the reduced model is in the controllable or observable canonical form. The [image omitted]-norm of the error between the original model and the reduced model is considered. Examples illustrate the application of the proposed method.

Improving image classification through descriptor combination

The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different feature vectors, we model the descriptor combination as an optimization problem to be addressed by evolutionary-based techniques, which compute distances between samples that maximize their separability in the feature space. The robustness of the proposed technique is assessed by the Optimum-Path Forest classifier. Experiments showed that the proposed methodology can outperform individual information provided by single descriptors in well-known public datasets. © 2012 IEEE.

Image quality evaluation of chest for computed radiography

The daily-to-day of medical practice is marked by a constant search for an accurate diagnosis and therapeutic assessment. For this purpose the doctor serves up a wide variety of imaging techniques, however, the methods using ionizing radiation still the most widely used because it is considered cheaper and above all very efficient when used with control and quality. The optimization of the risk-benefit ratio is considered a major breakthrough in relation to conventional radiology, though this is not the reality of computing and digital radiology, where Brazil has not established standards and protocols for this purpose. This work aims to optimize computational chest radiographs (anterior-posterior projection-AP). To achieve this objective were used a homogeneous phantoms that simulate the characteristics of absorption and scattering of radiation close to the chest of a patient standard. Another factor studied was the subjective evaluation of image quality, carried out by visual grading assessment (VGA) by specialists in radiology, using an anthropomorphic phantom to identify the best image for a particular pathology (fracture or pneumonia). Quantifying the corresponding images indicated by the radiologist was performed from the quantification of physical parameters (Detective Quantum Efficiency - DQE, Modulation Transfer Function - MTF and Noise Power Spectrum - NPS) using the software MatLab®. © 2013 Springer-Verlag.

Influence of cone-beam computed tomography image artifacts on the determination of dental arch measurements

Objective: To compare dental plaster model (DPM) and cone-beam computed tomography (CBCT) in the measurement of the dental arches, and investigate whether CBCT image artifacts compromise the reliability of such measurements.Materials and Methods: Twenty patients were divided into two groups based on the presence or absence of metallic restorations in the posterior teeth. Both dental arches of the patients were scanned with the CBCT unit i-CAT, and DPMs were obtained. Two examiners obtained eight arch measurements on the CBCT images and DPMs and repeated this procedure 15 days later. The arch measurements of each patient group were compared separately by the Wilcoxon rank sum (Mann-Whitney U) test, with a significance level of 5% (alpha = .05). Intraclass correlation measured the level of intraobserver agreement.Results: Patients with healthy teeth showed no significant difference between all DPM and CBCT arch measurements (P > .05). Patients with metallic restoration showed significant difference between DPM and CBCT for the majority of the arch measurements (P > .05). The two examiners showed excellent intraobserver agreement for both measuring methods with intraclass correlation coefficient higher than 0.95.Conclusion: CBCT provided the same accuracy as DPM in the measurement of the dental arches, and was negatively influenced by the presence of image artifacts.

Cardiomyopathy and cell therapy: ejection fraction improvement and cardiac muscle mass increasing, after a year of bone marrow stem cells transplantation, by magnetic resonance image

The idiopathic dilated cardiomyopathy (IDC) is one of the major public health problems in the western world. Patients with IDC in functional class IV (New York Health Association - NYHA), even after therapeutic optimization, have high mortality. Stem cell therapy has emerged as a potential therapeutic option for cell death-related heart diseases and several positive effects were assigned to cell therapy in cardiomyopathy. The aim of this study was identify short-term result of cell transplantation in idiopathic dilated cardiomyopathy patients (IDC) who were treated by transplantation of autologous bone marrow mononuclear cells (BMMC). Intracoronary injections of autologous BMMC were performed in eight patients with severe ventricle dysfunction (mean of left ventricle ejection fraction – LEVF=20.03%), cardiac mass muscle around 156.2 g and NYHA between III and IV grades, other 8 IDC patients received placebo. The IDCs were followed - up for one and two years, by magnetic resonance imaging (MRI). The results after one year showed significant improvement in LVEF (mean=181.4) and muscle mass increasing (mean=181.4 g), after two years the LVEF continued improving, reaching a mean of 32.69% and the cardiac muscle mass kept stable (mean=179.4 g). Excepted for one patient, all the other had improvement in the NYHA functional class. The placebo group did not show any improvement. We believe that BMMC implant may be a beneficial therapeutic option for IDC patients.