Sand fraction, organic carbon and nitrogen data, and calculated marine and terrestrial organic carbon fractions of surface sediments in the western Barents Sea

There is generally a lack of knowledge on how marine organic carbon accumulation is linked to vertical export and primary productivity patterns. In this study, a multi-proxy geochemical and organic-sedimentological approach is coupled with organic facies modelling focusing on regional calculations of carbon cycling and carbon burial on the western Barents Shelf between northern Scandinavia and Svalbard. OF-Mod 3D, an organic facies modelling software tool, is used to reconstruct the marine and terrestrial organic carbon fractions and to make inferences about marine primary productivity in this region. The model is calibrated with an extensive sample dataset and reproduces the present-day regional distribution of the organic carbon fractions well. Based on this new organic facies model, we present regional carbon mass accumulation rate calculations for the western Barents Sea. The calibration dataset includes location and water depth, sand fraction, organic carbon and nitrogen data and calculated marine and terrestrial organic carbon fractions.

Efficient Model-based 3D Tracking by Using Direct Image Registration

This thesis deals with the problem of efficiently tracking 3D objects in sequences of images. We tackle the efficient 3D tracking problem by using direct image registration. This problem is posed as an iterative optimization procedure that minimizes a brightness error norm. We review the most popular iterative methods for image registration in the literature, turning our attention to those algorithms that use efficient optimization techniques. Two forms of efficient registration algorithms are investigated. The first type comprises the additive registration algorithms: these algorithms incrementally compute the motion parameters by linearly approximating the brightness error function. We centre our attention on Hager and Belhumeur’s factorization-based algorithm for image registration. We propose a fundamental requirement that factorization-based algorithms must satisfy to guarantee good convergence, and introduce a systematic procedure that automatically computes the factorization. Finally, we also bring out two warp functions to register rigid and nonrigid 3D targets that satisfy the requirement. The second type comprises the compositional registration algorithms, where the brightness function error is written by using function composition. We study the current approaches to compositional image alignment, and we emphasize the importance of the Inverse Compositional method, which is known to be the most efficient image registration algorithm. We introduce a new algorithm, the Efficient Forward Compositional image registration: this algorithm avoids the necessity of inverting the warping function, and provides a new interpretation of the working mechanisms of the inverse compositional alignment. By using this information, we propose two fundamental requirements that guarantee the convergence of compositional image registration methods. Finally, we support our claims by using extensive experimental testing with synthetic and real-world data. We propose a distinction between image registration and tracking when using efficient algorithms. We show that, depending whether the fundamental requirements are hold, some efficient algorithms are eligible for image registration but not for tracking.