Algorithms for super-resolution of images based on Sparse Representation and Manifolds

lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super­ resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.

Identidade e imagem da marca: uma análise comparativa em uma empresa do setor de serviços de telecomunicações

In a highly connected society, avid for information and technological innovations, constantly changing the consumption patterns, the brand management strategy occupies a growing place. Allied with the increased competition among companies, the brand that can differentiate in consumers’ minds becomes strong. This aspect is even more important in the service industry, where the consumer experience, the definition and support of the brand’s values are vital to the continued strength of both your identity and image. These aspects are seen as a process of communication in which the way the image is developed in the minds of consumers comes from how identity is constructed and transmitted to them (DE CHERNATONY; DRURY; SEGAL-HORN, 2004). Considering the dynamic and complex scenario, this study aims to identify and analyze the possible convergences or divergences between the identity built by the organization and the brand image perceived by consumers of a telecommunications services company. To achieve this objective, the model proposed by De Chernatony, Drury and Segal-Horn (2004) was used as a theoretical basis, which addresses the transformation of identity in brand image, specifically under the perspective of Pontes (2009). For him, customers are more motivated to buy and consume products that they believe that take a complementary image that they have of themselves, and proposes the existence of multiple selves: the perceived, which refers to the employees and the organization’s management opinions on the brand; the ideal, which deals with effective brand identity thought by its leaders, the vision of what it should be; social, which shows how managers think that consumers see it; the apparent, formed by the image of the brand by customers; and finally the real self, that would be an integrated composite of all of these visions. In this regard, a case study was made in a telecommunications company with regional actions, from a qualitative and quantitative approach. It was identified the company’s vision through semi-structured interviews with marketing managers and analysis of documents related to the brand strategy. The point of view of consumers was addressed for text mining techniques applied to internal unstructured data coming from the collection of posts made on Facebook and Twitter, related to the brand, and customer interaction with the company through these social networks. The results showed the importance of the concepts of identity and brand image, and how they are interrelated. Moreover, the qualitative analysis it was shown that the vision of marketing executives is quite close and in line with the Brand Book, showing that there is a cohesive and well disseminated speech internally in the organization. On the other hand, when evaluating the customer's point of view there was no specific comments on the brand, and it was not possible to identify the evaluation of Algar Telecom image by consumers. Nevertheless, other relevant aspects could be identified for the consolidation of the brand identity, as the occurrence of a number of complaints, especially regarding the internet as well as the concern of customers for the quality of the provision of services.