La generazione di modelli tridimensionali densi in ambito architettonico mediante la fotogrammetria digitale

The Italian territory offers a wide range of treasures in the field of Cultural Assets. This is a highly relevant property, which needs an accurate management and preservation performed by appropriate tools, also giving attention to the maintenance and safeguard from risk factors. Nowadays the increasing development of new digital technologies, added by remarkable steps forward got by the subject of Geomatic makes possible an efficient integration among different techniques, helped also by spread of solutions to improve the data import-export and transmission between different devices. The main objective of this thesis is to experience the photogrammetric restitution implemented in a commercial software of digital photogrammetry, in order to generate a dense 3D model of the facade of the Basilica Sant'Apollinare Nuovo in Ravenna. The 1st Chapter, after a general introduction regarding the 3D survey of Cultural Heritage and some considerations linked to the use of digital photogrammetry in this field, is focused to analyze the case of stereoscopic and the monoscopic approach. In particular, it develops the theme of close-range photogrammetry. The 2nd Chapter, exposes the theme of digital images, from color theory until their appearing on the monitor. The 3rd Chapter, develops the case study of the Basilica di Sant'Apollinare Nuovo, the historical, architectural and religious of the same. Also, it is examined the issue of photogrammetry and laser scanning of the case study. The final part of the same chapter, treats the processing of data processing the software Agisoft PhotoScan, in order to generate, by means of Structure from Motion technique, a digital geometric 3D model of the Basilica Facade. The digital model has been scaled on the basis of measurements made on the field. With the software it was possible to accomplish the three phases of the photogrammetric data processing: internal orientation, exterior orientation and restitution.

Compressed sensing in digital tomosynthesis reconstruction

In this work we study a model for the breast image reconstruction in Digital Tomosynthesis, that is a non-invasive and non-destructive method for the three-dimensional visualization of the inner structures of an object, in which the data acquisition includes measuring a limited number of low-dose two-dimensional projections of an object by moving a detector and an X-ray tube around the object within a limited angular range. The problem of reconstructing 3D images from the projections provided in the Digital Tomosynthesis is an ill-posed inverse problem, that leads to a minimization problem with an object function that contains a data fitting term and a regularization term. The contribution of this thesis is to use the techniques of the compressed sensing, in particular replacing the standard least squares problem of data fitting with the problem of minimizing the 1-norm of the residuals, and using as regularization term the Total Variation (TV). We tested two different algorithms: a new alternating minimization algorithm (ADM), and a version of the more standard scaled projected gradient algorithm (SGP) that involves the 1-norm. We perform some experiments and analyse the performance of the two methods comparing relative errors, iterations number, times and the qualities of the reconstructed images. In conclusion we noticed that the use of the 1-norm and the Total Variation are valid tools in the formulation of the minimization problem for the image reconstruction resulting from Digital Tomosynthesis and the new algorithm ADM has reached a relative error comparable to a version of the classic algorithm SGP and proved best in speed and in the early appearance of the structures representing the masses.