Esquemas Morfológicos Multiescala Basados en Operaciones de Top-Hat para Aplicaciones de Mejora y Fusión de Imágenes

En este trabajo de tesis se presentan aplicaciones de la morfología matemática multiescalar a la mejora de imágenes medicas, infrarrojas, visibles y su extensión a técnicas de fusión de imágenes visibles e infrarrojas. La transformada de top-hat clásica es una operación de la morfológica matemática que es utilizada en los procesos de mejora de contraste y fusión de imágenes. Pero esta operación genera saturaciones en el proceso de mejora de la imagen especialmente en los bordes de las imágenes. A lo largo de este trabajo se propone reducir el efecto de saturación en algoritmos basados en morfología matemática multiescalar utilizando diferentes estrategias en la transformada de Top-Hat. Además, estas variaciones fueron probadas en nuevos algoritmos basados en morfología matemática multiescalar aplicados a la mejora de contraste de imágenes médicas, imágenes infrarrojas e imágenes visibles y en técnicas de fusión de imágenes visibles e infrarrojas. Los resultados obtenidos muestran imágenes médicas, infrarrojas, visibles e imágenes fusionadas con realce de contraste, mejora de detalles, preservación de brillo y bordes.CONACYT - Consejo Nacional de Ciencia y TecnologíaPROCIENCI

Non-Contact Evaluation Methods for Infrastructure Condition Assessment

The United States infrastructure, e.g. roads and bridges, are in a critical condition. Inspection, monitoring, and maintenance of these infrastructure in the traditional manner can be expensive, dangerous, time-consuming, and tied to human judgment (the inspector). Non-contact methods can help overcoming these challenges. In this dissertation two aspects of non-contact methods are explored: inspections using unmanned aerial systems (UASs), and conditions assessment using image processing and machine learning techniques. This presents a set of investigations to determine a guideline for remote autonomous bridge inspections

Computer aided detection of defects in FRP bridge decks using infrared thermography

The objective of this research is to develop a turn-key system that is able to interface with the FLIR ThermaCAM S60 infrared camera and automatically capture and analyze defects in infrared images of FRP bridge decks. Infrared thermography is one of the nondestructive evaluation (NDE) techniques that are being used to locate defects (debonds and delaminations) in bridge components. It is a rapid data collection and interpretation technique having high sensitivity and reliability. Analysis of infrared images by human interpretation is dependent on the users knowledge and hence introduces ambiguity in the defect detection process.;This thesis investigates the use of an automated defect detection system to locate defects in infrared images of FRP bridge decks to eliminate/reduce human intervention. Air-filled and water-filled debonds were inserted between the wearing surface and the underlying FRP deck. Also, simulated subsurface delaminations (of various sizes and thickness) were created at the flange-to-flange junction between two FRP deck modules. (Abstract shortened by UMI.)

People identification system with unmanned aerial vehicles

In this Bachelor's Degree Final Project, a mobile application for person identification using a DJI drone and the DJI Mobile SDK and DJI UX SDK software libraries is designed, implemented, and tested. The application tries to "identify" a specific person among those that are "detected" in the image. Our proposal, for this, is that the person who wants to be identified wears a GPS device to merge the information from the "people detector" with the "location" information provided by the GPS. The operation of the application mainly involves monitoring an MQTT server where different devices will upload their position using geodetic coordinates. Then, based on these coordinates, the application will perform a coordinate system transformation to obtain the pixel coordinates where the device is located. With these coordinates, the device's position can be overlaid on the video. Additionally, the application includes other visual functionalities such as a manager for photos and videos taken by the drone, a mini-map to visualize the drone's and surrounding devices' positions, a coordinate converter from screen points to geodetic coordinates, and the ability to write device data and drone position and attitude data to a text file. For the development of the application, various Software Development Kits (SDKs) are used, which provide the necessary resources for application development. Some of the SDKs used include the Android SDK, DJI UX SDK, and DJI Mobile SDK, with the latter two being from DJI. The MQTT protocol is used for message exchange between the drone and the different devices in the field. This protocol is based on centralized data exchange on a server and utilizes a publish-subscribe system. Furthermore, three different devices are used to obtain the user's location through GPS and send it to the MQTT server for the drone to access. One of these devices is created using a Raspberry Pi, another is an Android app, and the last one is based on a board from ArduSimple. Upon completing the application development, the project's initial objectives have been successfully achieved. A functional application has been programmed, and a device compatible with the specified requirements has been developed.Objectius de Desenvolupament Sostenible::16 - Pau, Justícia i Institucions Sòlide

A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community

In recent years, deep learning (DL), a re-branding of neural networks (NNs), has risen to the top in numerous areas, namely computer vision (CV), speech recognition, natural language processing, etc. Whereas remote sensing (RS) possesses a number of unique challenges, primarily related to sensors and applications, inevitably RS draws from many of the same theories as CV; e.g., statistics, fusion, and machine learning, to name a few. This means that the RS community should be aware of, if not at the leading edge of, of advancements like DL. Herein, we provide the most comprehensive survey of state-of-the-art RS DL research. We also review recent new developments in the DL field that can be used in DL for RS. Namely, we focus on theories, tools and challenges for the RS community. Specifically, we focus on unsolved challenges and opportunities as it relates to (i) inadequate data sets, (ii) human-understandable solutions for modelling physical phenomena, (iii) Big Data, (iv) non-traditional heterogeneous data sources, (v) DL architectures and learning algorithms for spectral, spatial and temporal data, (vi) transfer learning, (vii) an improved theoretical understanding of DL systems, (viii) high barriers to entry, and (ix) training and optimizing the DL.Comment: 64 pages, 411 references. To appear in Journal of Applied Remote Sensin

GRAPHOS – An open-source software for photogrammetric applications

19 p.This paper reports the latest developments for the photogrammetric open‐source tool called GRAPHOS (inteGRAted PHOtogrammetric Suite). GRAPHOS includes some recent innovations in the image‐based 3D reconstruction pipeline, from automatic feature detection/description and network orientation to dense image matching and quality control. GRAPHOS also has a strong educational component beyond its automated processing functions, reinforced with tutorials and didactic explanations about algorithms and performance. The paper highlights recent developments carried out at different levels: graphical user interface (GUI), didactic simulators for image processing, photogrammetric processing with weight parameters, dataset creation and system evaluationS

Design and performance assessment of correlation filters for the detection of objects in high clutter thermal imagery

The research reported in this thesis has examined means of enhancing the performance of the Optimal Trade-off Maximum Average Correlation Height (OT-MACH) filter for target detection in Forward Looking Infra-Red (FLIR) imagery acquired from a helicopter and border security FLIR camera in northern Kuwait. The data acquired with these FLIR sensors allows real-world evaluation of the comparative performance of the various filters that have been developed in the thesis. The results obtained have been quantified using well known performance measures such as Peak to Side-lobe Ratio (PSR) and Total Detection Error (TDE). The initial focus was to study the effect of modifying the OT-MACH parameters on the correlation metrics. A new optimisation technique has been presented, which computes statistically the filter alpha parameter associated with controlling the response of the filter to clutter noise. A further modification of the OT-MACH filter performance using the Difference of Gaussian bandpass filter (named the D-MACH filter) as a pre-processing stage has been described. The D-MACH has been applied to several test images containing single and multiple targets in the scene. Enhanced performance of the modified filter is demonstrated with improved metrics being obtained with less false side peaks in the correlation plane, especially when multiple targets are present in the test images. A further pre-processing technique was investigated using the Rayleigh distribution as a pre-processing filter (named the R-MACH filter). The R-MACH filter has been applied to multiple target types with tests conducted across various image data sets. The filter demonstrated an improvement over the Difference of Gaussian filter in terms of 6 reducing the number of parameters needing to be tuned whilst producing further enhanced correlation plane metrics. Finally, recommendations for future work has been made to improve the use of the OT-MACH filter in target detection and identification. A novel training image representation is proposed for further investigation, which will minimise the computational intensity of using the MACH filter for unconstrained object recognition

GRAPHOS - open-source software for photogrammetric applications

open11siThis work has been supported by ISPRS through the 2016 Scientific Initiative entitled Advances in the Development of an Open-source Photogrammetric Tool.This paper reports the latest developments for the photogrammetric open-source tool called GRAPHOS (inteGRAted PHOtogrammetric Suite). GRAPHOS includes some recent innovations in the image-based 3D reconstruction pipeline, from automatic feature detection/description and network orientation to dense image matching and quality control. GRAPHOS also has a strong educational component beyond its automated processing functions, reinforced with tutorials and didactic explanations about algorithms and performance. The paper highlights recent developments carried out at different levels: graphical user interface (GUI), didactic simulators for image processing, photogrammetric processing with weight parameters, dataset creation and system evaluation.embargoed_20190221Gonzalez-Aguilera, D.*; López-Fernández, L.; Rodriguez-Gonzalvez, P.; Hernandez-Lopez, D.; Guerrero, D.; Remondino, F.; Menna, F.; Nocerino, E.; Toschi, I.; Ballabeni, A.; Gaiani, M.Gonzalez-Aguilera, D.*; López-Fernández, L.; Rodriguez-Gonzalvez, P.; Hernandez-Lopez, D.; Guerrero, D.; Remondino, F.; Menna, F.; Nocerino, E.; Toschi, I.; Ballabeni, A.; Gaiani, M