Study of the effects of moving targets in SAR images for their detection.

Synthetic Aperture Radar’s (SAR) are systems designed in the early 50’s that are capable of obtaining images of the ground using electromagnetic signals. Thus, its activity is not interrupted by adverse meteorological conditions or during the night, as it occurs in optical systems. The name of the system comes from the creation of a synthetic aperture, larger than the real one, by moving the platform that carries the radar (typically a plane or a satellite). It provides the same resolution as a static radar equipped with a larger antenna. As it moves, the radar keeps emitting pulses every 1/PRF seconds —the PRF is the pulse repetition frequency—, whose echoes are stored and processed to obtain the image of the ground. To carry out this process, the algorithm needs to make the assumption that the targets in the illuminated scene are not moving. If that is the case, the algorithm is able to extract a focused image from the signal. However, if the targets are moving, they get unfocused and/or shifted from their position in the final image. There are applications in which it is especially useful to have information about moving targets (military, rescue tasks,studyoftheflowsofwater,surveillanceofmaritimeroutes...).Thisfeatureiscalled Ground Moving Target Indicator (GMTI). That is why the study and the development of techniques capable of detecting these targets and placing them correctly in the scene is convenient. In this document, some of the principal GMTI algorithms used in SAR systems are detailed. A simulator has been created to test the features of each implemented algorithm on a general situation with moving targets. Finally Monte Carlo tests have been performed, allowing us to extract conclusions and statistics of each algorithm.

Image Processing Challenges in the Creation of Spatiotemporal Gene Expression Atlases of Developing Embryos

To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

Image Processing Challenges in the Creation of Spatiotemporal Gene Expression Atlases of Developing Embryos

To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

Study of the effect of blurriness in image acquisition for Hand Biometrics in Mobile Devices

This paper presents a study on the effect of blurred images in hand biometrics. Blurred images simulates out-of-focus effects in hand image acquisition, a common consequence of unconstrained, contact-less and platform-free hand biometrics in mobile devices. The proposed biometric system presents a hand image segmentation based on multiscale aggregation, a segmentation method invariant to different changes like noise or blurriness, together with an innovative feature extraction and a template creation, oriented to obtain an invariant performance against blurring effects. The results highlight that the proposed system is invariant to some low degrees of blurriness, requiring an image quality control to detect and correct those images with a high degree of blurriness. The evaluation has considered a synthetic database created based on a publicly available database with 120 individuals. In addition, several biometric techniques could benefit from the approach proposed in this paper, since blurriness is a very common effect in biometric techniques involving image acquisition.

Assembling models of embryo development: Image analysis and the construction of digital atlases

Digital atlases of animal development provide a quantitative description of morphogenesis, opening the path toward processes modeling. Prototypic atlases offer a data integration framework where to gather information from cohorts of individuals with phenotypic variability. Relevant information for further theoretical reconstruction includes measurements in time and space for cell behaviors and gene expression. The latter as well as data integration in a prototypic model, rely on image processing strategies. Developing the tools to integrate and analyze biological multidimensional data are highly relevant for assessing chemical toxicity or performing drugs preclinical testing. This article surveys some of the most prominent efforts to assemble these prototypes, categorizes them according to salient criteria and discusses the key questions in the field and the future challenges toward the reconstruction of multiscale dynamics in model organisms.

Acoustic characterization of open cavities with the image source model

El objetivo de esta tesis es investigar las resonancias acústicas de una cavidad abierta tridimensional, de paredes rectas o inclinadas, mediante un método rápido y eficiente en el dominio del tiempo. Este método modela la respuesta temporal en cualquier punto como la convolución de la forma de onda de la fuente con la respuesta impulsiva de la cavidad, la cual se obtiene como una secuencia de impulsos retardados y atenuados procedentes de la fuente real, el primero, y de las fuentes imágenes especulares, los siguientes (Modelo Fuente Imagen, ISM). Además de las componentes directa y reflejadas en las paredes, la respuesta impulsiva también incluye las contribuciones difractadas en los bordes, obtenidas mediante la generación de las componentes difractadas de cada fuente imagen. Las frecuencias de resonancia acústica de la cavidad abierta son extraídas de los picos de la Función de Respuesta en Frecuencia (FRF), obtenida como la transformada de Fourier de la respuesta temporal correspondiente entre una fuente puntual y un punto cualquiera de la cavidad. Las frecuencias de resonancia acústicas estimadas mediante este Método de Fuentes Imagen + difracción en bordes son validadas por comparación con las que proporciona un Modelo de Elementos Finitos (FEM) y con las medidas experimentalmente, con diferencias menores que el 1.6 % y el 2.7 %, respectivamente. A modo de comparación, las frecuencias de resonancia estimadas para la misma cavidad por el método ISM, cuando no se incluye la difracción en los bordes, difieren en un 5.7 % de las obtenidas experimentalmente. ABSTRACT The goal of this thesis is to investigate the acoustic resonances of a three-dimensional open cavity, with parallel and non-parallel walls, by a fast and efficient method in the time domain. This method models the time response in any point as the convolution of the source waveform with the impulse response of the cavity, which, in turn, is obtained as a sequence of attenuated and delayed impulses coming, the first from the real, and the subsequent from the mirror imaged sources (Image Source Model). Besides direct and wall-reflected components, the impulse response includes also edge-diffracted contributions by generating first order diffraction components for each image source. The acoustic resonance frequencies of the open cavity are extracted from the peaks of the Frequency Response Function (FRF), obtained as the Fourier transform of the corresponding time response between a point source and any point in the cavity. The acoustic resonance frequencies estimated by the Image Source Model + edge diffraction are validated by comparison with those provided by a Finite Element Model (FEM) and the ones measured experimentally, differing less than 1.6 % and 2.7 %, respectively. As a comparison, resonance frequencies estimated with the pure Image Source Model differ by 5.7 % from the measured ones.