Sparse image representation with encryption

In this thesis we present an overview of sparse approximations of grey level images. The sparse representations are realized by classic, Matching Pursuit (MP) based, greedy selection strategies. One such technique, termed Orthogonal Matching Pursuit (OMP), is shown to be suitable for producing sparse approximations of images, if they are processed in small blocks. When the blocks are enlarged, the proposed Self Projected Matching Pursuit (SPMP) algorithm, successfully renders equivalent results to OMP. A simple coding algorithm is then proposed to store these sparse approximations. This is shown, under certain conditions, to be competitive with JPEG2000 image compression standard. An application termed image folding, which partially secures the approximated images is then proposed. This is extended to produce a self contained folded image, containing all the information required to perform image recovery. Finally a modified OMP selection technique is applied to produce sparse approximations of Red Green Blue (RGB) images. These RGB approximations are then folded with the self contained approach.

Design and designing:a critical introduction

Design and Designing provides a broad and critical understanding of what is essentially a practical subject. Designing today is less a craft and more a part of the knowledge economy. It's all about knowing how to acquire knowledge and how to apply it creatively. Design and Designing covers the design process, modelling and drawing, working with clients, production and consumption, sustainability, professional practice and design futures. Chapters are written by expert teachers and practitioners from around the globe, each presenting an accessible and engaging overview of their field of design. Every chapter is highly illustrated with a combination of images and information boxes, which extend or highlight key material. Each section concludes with a design project, a hands-on activity for the reader. Design and Designing covers the full spectrum of design types, from graphic communication to product design, from fashion to games design, setting every type in its aesthetic, ethical and social contexts. With this essential book, readers will learn from today's best practice and best thinking in design, they will develop a critical sense, and become the designers of tomorrow.

Fitness and novelty in evolutionary art

In this paper the effects of introducing novelty search in evolutionary art are explored. Our algorithm combines fitness and novelty metrics to frame image evolution as a multi-objective optimisation problem, promoting the creation of images that are both suitable and diverse. The method is illustrated by using two evolutionary art engines for the evolution of figurative objects and context free design grammars. The results demonstrate the ability of the algorithm to obtain a larger set of fit images compared to traditional fitness-based evolution, regardless of the engine used.

No-reference image quality assessment in contourlet domain

The target of no-reference (NR) image quality assessment (IQA) is to establish a computational model to predict the visual quality of an image. The existing prominent method is based on natural scene statistics (NSS). It uses the joint and marginal distributions of wavelet coefficients for IQA. However, this method is only applicable to JPEG2000 compressed images. Since the wavelet transform fails to capture the directional information of images, an improved NSS model is established by contourlets. In this paper, the contourlet transform is utilized to NSS of images, and then the relationship of contourlet coefficients is represented by the joint distribution. The statistics of contourlet coefficients are applicable to indicate variation of image quality. In addition, an image-dependent threshold is adopted to reduce the effect of content to the statistical model. Finally, image quality can be evaluated by combining the extracted features in each subband nonlinearly. Our algorithm is trained and tested on the LIVE database II. Experimental results demonstrate that the proposed algorithm is superior to the conventional NSS model and can be applied to different distortions. © 2009 Elsevier B.V. All rights reserved.

Manifold learning and the quantum Jensen-Shannon divergence kernel

The quantum Jensen-Shannon divergence kernel [1] was recently introduced in the context of unattributed graphs where it was shown to outperform several commonly used alternatives. In this paper, we study the separability properties of this kernel and we propose a way to compute a low-dimensional kernel embedding where the separation of the different classes is enhanced. The idea stems from the observation that the multidimensional scaling embeddings on this kernel show a strong horseshoe shape distribution, a pattern which is known to arise when long range distances are not estimated accurately. Here we propose to use Isomap to embed the graphs using only local distance information onto a new vectorial space with a higher class separability. The experimental evaluation shows the effectiveness of the proposed approach. © 2013 Springer-Verlag.

Whether social schema violations help or hurt creativity depends on need for structure

Although people and events that disconfirm observers' expectancies can increase their creativity, sometimes such social schema violations increase observers' rigidity of thought and undermine creative cognition. Here we examined whether individual differences in the extent to which people prefer structure and predictability determine whether social schema violations facilitate or hamper creativity. Participants in Study 1 formed impressions of a schema-inconsistent female mechanic (vs. a schema-consistent male mechanic). Following schema-inconsistent rather than -consistent information, participants low (high) in need for structure showed better (impeded) creative performance. Participants in Study 2 memorized a series of images in which individuals were placed on a schema-inconsistent (vs. consistent) background (e.g., an Eskimo on the desert vs. on a snowy landscape). Following schema-inconsistent imagery, participants low (high) in need for structure increased (decreased) divergent thinking. © 2014 by the Society for Personality and Social Psychology, Inc.