Mapping probabilities of precipitation occurrence on the territory of the Republic of Serbia by the method of indicator kriging

This paper presents the application of indicator kriging as a geostatistical method for the purpose of creating maps of precipitation occurrence probabilities on the territory of the Republic of Serbia for distinctive months during 2009. The difference between this approach to mapping and standard isohyetal maps, which describe precipitation intensity, lies in the fact that this approach points to the potential of the occurrence of a certain amount of precipitation at a specific location for a given time period. [Projekat Ministarstva nauke Republike Srbije, br. III 47014, br. TR 36009 i br. III 43007

The possibilities of application of 3D digital models in cultural heritage objects' protection and revitalisation

Contemporary cultural heritage protection relies on precise technical documentation obtained by new technology accomplishments in the domain of 3D digital models. Both 3D models of the existing state of object and virtual ones are equally important in reconstruction and renewal processes. Accurate, textured and detailed 3D point cloud models of various objects, i.e. cultural heritage monuments, are outcomes of contemporary photogrammetric and laser scanning methods, aided by adequate software solutions. The authors presented procedures and results of terrestrial laser scanning and 3D modelling of a cultural heritage monument the monastery church of the complex Kastaljan, located in the mountain region Kosmaj in Serbia. The first part of presented research, concerning data acquisition, carried out using laser scanner and adequate software processing, resulted in 3D dense point cloud model and further 2D plan view along with characteristic cross sections. The possibilities of 3D model presentation, measurements and additional graphic operations were explored, through various software solutions aided by adequate technical support. The second part of research elaborated on the reconstruction of the entire 3D model of the church in the complex Kastaljan, dated back to the 13th century, according to its architectural style characteristics

Lesion Focused Super-Resolution

Super-resolution (SR) for image enhancement has great importance in medical image applications. Broadly speaking, there are two types of SR, one requires multiple low resolution (LR) images from different views of the same object to be reconstructed to the high resolution (HR) output, and the other one relies on the learning from a large amount of training datasets, i.e., LR-HR pairs. In real clinical environment, acquiring images from multi-views is expensive and sometimes infeasible. In this paper, we present a novel Generative Adversarial Networks (GAN) based learning framework to achieve SR from its LR version. By performing simulation based studies on the Multimodal Brain Tumor Segmentation Challenge (BraTS) datasets, we demonstrate the efficacy of our method in application of brain tumor MRI enhancement. Compared to bilinear interpolation and other state-of-the-art SR methods, our model is lesion focused, which is not only resulted in better perceptual image quality without blurring, but also more efficient and directly benefit for the following clinical tasks, e.g., lesion detection and abnormality enhancement. Therefore, we can envisage the application of our SR method to boost image spatial resolution while maintaining crucial diagnostic information for further clinical tasks.Comment: 4 pages, 2 figures, 1 table, Accepted as Oral Presentation by the SPIE Medical Imaging Conference 201

Optimizacija drugog reda geodetske mreže korišćenjem različitih kriterijum matrica TK strukture

Geodetic network design for numerous practical applications (surveying, staking out of characteristic points of an object in construction, control of geometry of a built-up object, monitoring, etc) represents a problem which requires implementation of well-known optimization methods. Optimization aim is establishing as much accurate and reliable geodetic network as possible with as less costs as possible. Geodetic network optimization is classified into different orders but in this paper only the second order design which deals with the determination of the weights of network measurements is presented. Within the second order design it is necessary to form a criterion matrix which substitutes real covariance matrix and to define observation scheme in network. The criterion matrix is formed by using one of the correlation functions whose arguments are distances between geodetic network points. This paper presents comparative analysis of the results of the second order design of trilateration geodetic network. These results were obtained by using TK-structured criterion matrices formed by using Gaussian and Baarda’s correlation functions of point coordinates. As it was expected, Gaussian correlation function is the one that proved as a better choice because it generally adapts better to the geodetic network requirements than Baarda’s correlation function: the results obtained by using Gaussian correlation function tolerate less accurate distance measurements.Projektovanje geodetske mreže za razne potrebe u praksi (premer, obeležavanje karakterističnih tačaka nekog objekta u izgradnji, kontrola geometrije izgrađenog objekta, monitoring, itd.) predstavlja problem koji zahteva primenu poznatih metoda optimizacije. Cilj optimizacije je uspostavljanje geodetske mreže sa što većom pouzdanošću, tačnošću i uz što manje troškove. Optimizacija projektovanja geodetskih mreža klasifikuje se u različite redove ali je u okviru rada prikazana samo optimizacija drugog reda koja podrazumeva određivanje optimalnih težina planiranih merenja u geodetskoj mreži. U okviru optimizacije drugog reda neophodno je formirati kriterijum matricu koja zamenjuje realnu kovarijacionu matricu i definisati plan opažanja u mreži. Kriterijum matrica se formira na osnovu neke korelacione funkcije koordinata tačaka čiji su argumenti dužine između tačaka geodetske mreže. U radu je izvršena uporedna analiza rezultata optimizacije drugog reda trilateracione geodetske mreže dobijenih korišćenjem kriterijum matrica TK strukture,koje su formirane na osnovu Gausove i Bardine korelacione funkcije koordinata tačaka. Kao što se i očekivalo, Gausova korelaciona funkcija se pokazala kao bolji izbor prilikom kreiranja kriterijum matrice kofaktora jer zbog njene bolje prilagodljivosti uslovima koje geodetska mreža treba da ispuni (u odnosu na Bardinu korelacionu funkciju), dobijeni odgovarajući rezultati optimizacije dopuštaju merenje dužina sa manjom tačnošću

Optimizacija drugog reda geodetske mreže korišćenjem različitih kriterijum matrica TK strukture

Geodetic network design for numerous practical applications (surveying, staking out of characteristic points of an object in construction, control of geometry of a built-up object, monitoring, etc) represents a problem which requires implementation of well-known optimization methods. Optimization aim is establishing as much accurate and reliable geodetic network as possible with as less costs as possible. Geodetic network optimization is classified into different orders but in this paper only the second order design which deals with the determination of the weights of network measurements is presented. Within the second order design it is necessary to form a criterion matrix which substitutes real covariance matrix and to define observation scheme in network. The criterion matrix is formed by using one of the correlation functions whose arguments are distances between geodetic network points. This paper presents comparative analysis of the results of the second order design of trilateration geodetic network. These results were obtained by using TK-structured criterion matrices formed by using Gaussian and Baarda’s correlation functions of point coordinates. As it was expected, Gaussian correlation function is the one that proved as a better choice because it generally adapts better to the geodetic network requirements than Baarda’s correlation function: the results obtained by using Gaussian correlation function tolerate less accurate distance measurements.Projektovanje geodetske mreže za razne potrebe u praksi (premer, obeležavanje karakterističnih tačaka nekog objekta u izgradnji, kontrola geometrije izgrađenog objekta, monitoring, itd.) predstavlja problem koji zahteva primenu poznatih metoda optimizacije. Cilj optimizacije je uspostavljanje geodetske mreže sa što većom pouzdanošću, tačnošću i uz što manje troškove. Optimizacija projektovanja geodetskih mreža klasifikuje se u različite redove ali je u okviru rada prikazana samo optimizacija drugog reda koja podrazumeva određivanje optimalnih težina planiranih merenja u geodetskoj mreži. U okviru optimizacije drugog reda neophodno je formirati kriterijum matricu koja zamenjuje realnu kovarijacionu matricu i definisati plan opažanja u mreži. Kriterijum matrica se formira na osnovu neke korelacione funkcije koordinata tačaka čiji su argumenti dužine između tačaka geodetske mreže. U radu je izvršena uporedna analiza rezultata optimizacije drugog reda trilateracione geodetske mreže dobijenih korišćenjem kriterijum matrica TK strukture,koje su formirane na osnovu Gausove i Bardine korelacione funkcije koordinata tačaka. Kao što se i očekivalo, Gausova korelaciona funkcija se pokazala kao bolji izbor prilikom kreiranja kriterijum matrice kofaktora jer zbog njene bolje prilagodljivosti uslovima koje geodetska mreža treba da ispuni (u odnosu na Bardinu korelacionu funkciju), dobijeni odgovarajući rezultati optimizacije dopuštaju merenje dužina sa manjom tačnošću

TLS data georeferencing - error sources and effects

Depending on the requirements of a certain engineering task, point coordinates obtained through terrestrial laser scanning (TLS) can be either in a scanner coordinate system (CS) or in the coordinate system of a geodetic control network. When point coordinates in some external CS are needed point cloud georeferencing must be done, i.e. point coordinates have to be transformed from the scanner CS into the desired CS.Different procedures can be followed during the transformation process of point coordinates from one CS to the other and consequently it can be distinguished between several types of georeferencing. The principal classification is into direct and indirect georeferencing and the main difference between the two is that direct georeferencing can (and usually does) give point coordinates in the CS of a geodetic control network instantly in the field, while indirect georeferencing inevitably needs some work to be done in the office in order to obtain these coordinates. Indirect georeferencing is necessarily done in some software and it distinguishes between the process itself being completed in either one or two steps. On the other hand, direct georeferencing does not involve transformation into some intermediate CS whichis the case with the two-step indirect georeferencing. Direct georeferencing essentially mimics the procedure of orienting a total station with respect to a geodetic control network which can be achieved either through backsighting (the “station-orientation” procedure) or resection.This paper briefly presents different georeferencing procedures and related main error sources that cause errors in transformed point coordinates. Additionally, the covariance model for direct georeferencing following the “station-orientation” procedure is verified through statistical analysis of the data collected in the experiment performed in the field. True point position errors calculated as differences between point coordinates obtained from the least squares adjustment of the geodetic control network and those from direct georeferencing of the TLS data are compared with theoretical errors, i.e. model-derived standard deviations of point positions. It is shown that these two setsof errors or, more precisely, the variance of the true errors and the pooled model-derived variance of the control point positions do not feature a significant difference at the confidence level of 99%. This makes us optimistic in terms of possibility of using the reported model for predicting trueerrors of point positions by model-derived standard deviations obtained as a result of direct georeferencing of TLS data following the “station-orientation” procedure