Fast, Accurate and Consistent Modeling of Drainage and Surrounding Terrain

We propose an automated approach to modeling drainage channels and, more generally, linear features that lie on the terrain|from multiple images. It produces models of the features and of the surrounding terrain that are accurate and consistent and requires only minimal human intervention. We take advantage of geometric constraints and photommetric knowledge. First, rivers flow downhill and lie at the bottom valleys whose floors tend to be either V- or U-shaped. Second, the drainage pattern appears in gray-level images as a network of linear features that can be visually detected. Many approaches have explored individual facets of this problem. Ours unifies these elements in a common framework. We accurately model terrain and features as 3-dimensional ob jects from several information sources that may be in error and inconsistent with one another. This approach allows us to generate models that are faithful to sensor data, internally consistent and consistent with physical constraints. We have proposed generic models that have been applied to the specific task at hand. We show that the constraints can be expressed in a computationally effective way and, therefore, enforced while initializing the models and then fitting them to the data. Furthermore, these techniques are general enough to work on other features that are constrained by predictable forces

A Parallel Stereo Algorithm that Produces Dense Depth Maps and Preserves Image Features

We have developed a stereo algorithm that relies on grey level correlation followed by interpolation using an energy based technique. During the correlation phase the two images play a symmetric role and we use a validity criterion for the matches that eliminates the gross errors: when the images cannot be correlated reliably, due to lack of texture or occlusions for example, the algorithm does not produce wrong matches but a very sparse disparity map as opposed to a dense one when the correlation is successful and we argue that the density of the map is a good estimate of its reliability. To generate dense depth map, the information is then propagated across the featureless areas but not across discontinuities by an interpolation algorithm that takes image grey levels to preserve image features

Model-Based Optimization: Accurate and Consistent Site Modeling

Governance of innovation – deploying an architectural framework for innovation of technological systems for energy, security and defence Innovation has a great deal of attraction but is associated with serious uncertainties and downsides. It is potentially beneficial for growth, sector and industrial development and competitiveness. Innovation brings hope of solving societal challenges, such as climate change and environment protection, and could help secure a supply of energy. Furthermore, it improves resilience and strengthens security and defence. The downside of innovations of some magnitude concern severe transitions and disruptions. Digitisation, with associated net technologies, is an illustrative example of an innovation that creates new services, competitiveness and other benefits which is enormously positive and attractive, while simultaneously dismantles and destroys existing systems, firms and branches, and whole sectors and practices. The thesis deals with promoting innovations at large but specifically systemic, defined as a value-adding (to customers and users) set or convergence of new products/services from technological systems in processes which emerge by evolutionary association and integration of systems transforming businesses, industries and sectors (with disruptions as consequence). Innovations are distinguished by certain structural properties namely systemicitiness. The systemicitiness of innovations suggests a distinct architectural framework that determines the structure of innovations. The purpose of the proposal for an architectural framework for innovation is guidance to governance of innovation. Platform based ecosystems exemplifies an emulation of systemic innovation that aligns with the proposed framework. The framework is distilled from cases, events, patterns, landscapes and models of innovation in the literature, connected with examination of systemicitiness and governance approaches to innovation and innovation processes. The architectural framework is conjected as compatible and complementary to common policies and instruments for innovation and innovation processes as holistic systems engineering, standards and protocols (e.g. ISO/IEC 15288:2015, ISO/IEC 42010:2011, NISP)