Propagation, structural similarity and image quality

Póster presentado en SPIE Photonics Europe, Brussels, 16-19 April 2012.

Retinal image quality assessment through a visual similarity index

Retinal image quality is commonly analyzed through parameters inherited from instrumental optics. These parameters are defined for ‘good optics’ so they are hard to translate into visual quality metrics. Instead of using point or artificial functions, we propose a quality index that takes into account properties of natural images. These images usually show strong local correlations that help to interpret the image. Our aim is to derive an objective index that quantifies the quality of vision by taking into account the local structure of the scene, instead of focusing on a particular aberration. As we show, this index highly correlates with visual acuity and allows inter-comparison of natural images around the retina. The usefulness of the index is proven through the analysis of real eyes before and after undergoing corneal surgery, which usually are hard to analyze with standard metrics.

Structural similarity of directed universal hierarchical graphs: A low computational complexity approach

In the present paper we mainly introduce an efficient approach to measure the structural similarity of so called directed universal hierarchical graphs. We want to underline that directed universal hierarchical graphs can be obtained from generalized trees which are already introduced. In order to classify these graphs, we state our novel graph similarity method. As a main result we notice that our novel algorithm has low computational complexity. (c) 2007 Elsevier Inc. All rights reserved.

Mouse alarm pheromone shares structural similarity with predator scents.

Sensing the chemical warnings present in the environment is essential for species survival. In mammals, this form of danger communication occurs via the release of natural predator scents that can involuntarily warn the prey or by the production of alarm pheromones by the stressed prey alerting its conspecifics. Although we previously identified the olfactory Grueneberg ganglion as the sensory organ through which mammalian alarm pheromones signal a threatening situation, the chemical nature of these cues remains elusive. We here identify, through chemical analysis in combination with a series of physiological and behavioral tests, the chemical structure of a mouse alarm pheromone. To successfully recognize the volatile cues that signal danger, we based our selection on their activation of the mouse olfactory Grueneberg ganglion and the concomitant display of innate fear reactions. Interestingly, we found that the chemical structure of the identified mouse alarm pheromone has similar features as the sulfur-containing volatiles that are released by predating carnivores. Our findings thus not only reveal a chemical Leitmotiv that underlies signaling of fear, but also point to a double role for the olfactory Grueneberg ganglion in intraspecies as well as interspecies communication of danger.

The relationship between L3 transfer and structural similarity across L3 development: raising across an experience in Brazilian Portuguese

The present study examines three competing models of morphosyntactic transfer in third language (L3) acquisition, examining the particular domain of the feature configuration of embedded T in L3 Brazilian Portuguese (BP) at the initial stages and then through development. The methodology alternates Spanish and English as the L1 and L2 to tease apart the source of transfer to L3 BP. Results from a scalar grammaticality acceptability task show unequivocal transfer of Spanish irrespective of Spanish’s status as an L1 or L2. The data thus support the Typological Primacy Model (Rothman 2010, 2011, 2013a, 2013b), which proposes that multilingual transfer is selected by factors related to comparative structural similarity. Given that Spanish transfer at the L3 initial stages creates the need for feature reconfiguration to converge on the target BP grammar, the second part of this chapter examines the developmental consequences of what the TPM models in cases of non-facilitative initial transfer, that is, the developmental path of feature reconfiguration of embedded T in L3 BP by English/Spanish bilinguals. Given what these data reveal, we address the role of regressive transfer as a correlate of L3 proficiency gains.

Entropy Constrained Exemplar-based Image Inpainting

Image inpainting is the process of filling the unwanted region in an image marked by the user. It is used for restoring old paintings and photographs, removal of red eyes from pictures, etc. In this paper, we propose an efficient inpainting algorithm which takes care of false edge propagation. We use the classical exemplar based technique to find out the priority term for each patch. To ensure that the edge content of the nearest neighbor patch found by minimizing L-2 distance between patches, we impose an additional constraint that the entropy of the patches be similar. Entropy of the patch acts as a good measure of edge content. Additionally, we fill the image by considering overlapping patches to ensure smoothness in the output. We use structural similarity index as the measure of similarity between ground truth and inpainted image. The results of the proposed approach on a number of examples on real and synthetic images show the effectiveness of our algorithm in removing objects and thin scratches or text written on image. It is also shown that the proposed approach is robust to the shape of the manually selected target. Our results compare favorably to those obtained by existing techniques

l(1)-K-SVD: A robust dictionary learning algorithm with simultaneous update

We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.

Avaliação de imagens através de Similaridade Estrutural e do conceito de Mínima Diferença de Cor Perceptível.

A avaliação objetiva da qualidade de imagens é de especial importância em diversas aplicações, por exemplo na compressão de imagens, onde pode ser utilizada para regular a taxa que deve ser empregada para que haja a máxima compressão (permitindo perda de dados) sem comprometer a qualidade final; outro exemplo é na inserção de marcas dágua, isto é, introdução de informações descritivas utilizadas para atestar a autenticidade de uma imagem, que devem ser invisíveis para o observador. O SSIM (Structural SIMilarity) é uma métrica de avaliação objetiva da qualidade de imagens de referência completa projetada para imagens em tons de cinza. Esta dissertação investiga sua aplicação na avaliação de imagens coloridas. Para tanto, inicialmente é feito um estudo do SSIM utilizando quatro diferentes espaços de cores RGB, YCbCr, Lαβ e CIELAB. O SSIM é primeiramente calculado nos canais individuais desses espaços de cores. Em seguida, com inspiração no trabalho desenvolvido em (1) são testadas formas de se combinar os valores SSIM obtidos para cada canal em um valor único os chamados SSIM Compostos. Finalmente, a fim de buscar melhores correlações entre SSIM e avaliação subjetiva, propomos a utilização da mínima diferença de cor perceptível, calculada utilizando o espaço de cores CIELAB, conjuntamente com o SSIM. Para os testes são utilizados três bancos de dados de imagens coloridas, LIVE, IVC e TID, a fim de se conferir consistência aos resultados. A avaliação dos resultados é feita utilizando as métricas empregadas pelo VQEG (Video Quality Experts Group) para a avaliação da qualidade de vídeos, com uma adaptação. As conclusões do trabalho sugerem que os melhores resultados para avaliação da qualidade de imagens coloridas usando o SSIM são obtidas usando os canais de luminância dos espaços de cores YCbCr, Lαβ e especialmente o CIELAB. Também se concluiu que a utilização da mínima diferença de cor perceptível contribui para o melhoramento dos resultados da avaliação objetiva.

Arcabouço para aprovisionamento de QoS e QoE em redes sem fio heterogêneas WiMAX/Wi-Fi com garantia de equidade entre vazões

Recentemente a sociedade está vivendo em meio a um aglomerado de dispositivos móveis com múltiplas interfaces sem fio que permitem que clientes móveis domésticos e corporativos solucionem problemas rotineiros no menor espaço de tempo e em diversas localizações. Por outro lado, a disponibilidade de diversas tecnologias de acesso sem fio como: Wi-Fi (Wireless Fidelity), WiMAX (Worldwide Interoperability for Microwave Access) e LTE (Long Term Evolution), proporcionam um cenário heterogêneo com diversas oportunidades de conectividade para o usuário de dispositivos com múltiplas interfaces. Alguns dos desafios atuais no contexto da concepção da então denominada NGN (Next Generation Networks) são o desenvolvimento de arcabouços e mecanismos que viabilizem tanto o suporte adequado à Qualidade de Serviço (QoS – Quality of Service) e à Qualidade de Experiência (QoE – Quality of Experience) para aplicações multimídia, quanto a garantia de equidade entre vazões de diferentes aplicações em ambiente heterogêneo. Esta dissertação propõe um arcabouço para o aprovisionamento de QoS e QoE em redes sem fio heterogêneas formada por redes WiMAX e Wi-Fi. Especificamente, nossa solução provê mapeamento estático de QoS entre as classes de serviços WiMAX e categorias de acesso Wi-Fi. Além disso, nossa proposta também combina funcionalidades de equidade entre vazões com a solução de mapeamento, a fim de alcançar um bom compromisso tanto para o operador da rede, quanto para o usuário, através de uma nova metodologia de coleta e calculo de vazão agregada e algoritmo de decisão de handover vertical. A avaliação quantitativa da proposta foi realizada através de modelos de simulação no ns-2 (Network Simulator). Os resultados de desempenho demonstram a eficiência da arquitetura em termos de métricas de QoS (vazão, vazão média e atraso) e QoE (PSRN - Peak Signal to Noise Ratio, SSIM - Structural Similarity Index e VQM - Video Quality Metric).

Applying enhancement filters in the pre-processing of images of lymphoma

Lymphoma is a type of cancer that affects the immune system, and is classified as Hodgkin or non-Hodgkin. It is one of the ten types of cancer that are the most common on earth. Among all malignant neoplasms diagnosed in the world, lymphoma ranges from three to four percent of them. Our work presents a study of some filters devoted to enhancing images of lymphoma at the pre-processing step. Here the enhancement is useful for removing noise from the digital images. We have analysed the noise caused by different sources like room vibration, scraps and defocusing, and in the following classes of lymphoma: follicular, mantle cell and B-cell chronic lymphocytic leukemia. The filters Gaussian, Median and Mean-Shift were applied to different colour models (RGB, Lab and HSV). Afterwards, we performed a quantitative analysis of the images by means of the Structural Similarity Index. This was done in order to evaluate the similarity between the images. In all cases we have obtained a certainty of at least 75%, which rises to 99% if one considers only HSV. Namely, we have concluded that HSV is an important choice of colour model at pre-processing histological images of lymphoma, because in this case the resulting image will get the best enhancement.

A comparison of denoising methods for X-ray fluoroscopic images

Fluoroscopic images exhibit severe signal-dependent quantum noise, due to the reduced X-ray dose involved in image formation, that is generally modelled as Poisson-distributed. However, image gray-level transformations, commonly applied by fluoroscopic device to enhance contrast, modify the noise statistics and the relationship between image noise variance and expected pixel intensity. Image denoising is essential to improve quality of fluoroscopic images and their clinical information content. Simple average filters are commonly employed in real-time processing, but they tend to blur edges and details. An extensive comparison of advanced denoising algorithms specifically designed for both signal-dependent noise (AAS, BM3Dc, HHM, TLS) and independent additive noise (AV, BM3D, K-SVD) was presented. Simulated test images degraded by various levels of Poisson quantum noise and real clinical fluoroscopic images were considered. Typical gray-level transformations (e.g. white compression) were also applied in order to evaluate their effect on the denoising algorithms. Performances of the algorithms were evaluated in terms of peak-signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), mean square error (MSE), structural similarity index (SSIM) and computational time. On average, the filters designed for signal-dependent noise provided better image restorations than those assuming additive white Gaussian noise (AWGN). Collaborative denoising strategy was found to be the most effective in denoising of both simulated and real data, also in the presence of image gray-level transformations. White compression, by inherently reducing the greater noise variance of brighter pixels, appeared to support denoising algorithms in performing more effectively. © 2012 Elsevier Ltd. All rights reserved.

Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: Molecular docking and 3D QSAR studies

The glycolytic enzyme glyceraldehyde-3 -phosphate dehydrogenase (GAPDH) is as an attractive target for the development of novel antitrypanosomatid agents. In the present work, comparative molecular field analysis and comparative molecular similarity index analysis were conducted on a large series of selective inhibitors of trypanosomatid GAPDH. Four statistically significant models were obtained (r(2) > 0.90 and q(2) > 0.70), indicating their predictive ability for untested compounds. The models were then used to predict the potency of an external test set, and the predicted values were in good agreement with the experimental results. Molecular modeling studies provided further insight into the structural basis for selective inhibition of trypanosomatid GAPDH.

Sustainable Road Management in Texas : network-level flexible pavement structural condition analysis using data mining techniques

The research team recognized the value of network-level Falling Weight Deflectometer (FWD) testing to evaluate the structural condition trends of flexible pavements. However, practical limitations due to the cost of testing, traffic control and safety concerns and the ability to test a large network may discourage some agencies from conducting the network-level FWD testing. For this reason, the surrogate measure of the Structural Condition Index (SCI) is suggested for use. The main purpose of the research presented in this paper is to investigate data mining strategies and to develop a prediction method of the structural condition trends for network-level applications which does not require FWD testing. The research team first evaluated the existing and historical pavement condition, distress, ride, traffic and other data attributes in the Texas Department of Transportation (TxDOT) Pavement Maintenance Information System (PMIS), applied data mining strategies to the data, discovered useful patterns and knowledge for SCI value prediction, and finally provided a reasonable measure of pavement structural condition which is correlated to the SCI. To evaluate the performance of the developed prediction approach, a case study was conducted using the SCI data calculated from the FWD data collected on flexible pavements over a 5-year period (2005 – 09) from 354 PMIS sections representing 37 pavement sections on the Texas highway system. The preliminary study results showed that the proposed approach can be used as a supportive pavement structural index in the event when FWD deflection data is not available and help pavement managers identify the timing and appropriate treatment level of preventive maintenance activities.