Towards Detecting Changes in Underwater Image Sequences

Detecting changes between images of the same scene taken at different times is of great interest for monitoring and understanding the environment. It is widely used for on-land application but suffers from different constraints. Unfortunately, Change detection algorithms require highly accurate geometric and photometric registration. This requirement has precluded their use in underwater imagery in the past. In this paper, the change detection techniques available nowadays for on-land application were analyzed and a method to automatically detect the changes in sequences of underwater images is proposed. Target application scenarios are habitat restoration sites, or area monitoring after sudden impacts from hurricanes or ship groundings. The method is based on the creation of a 3D terrain model from one image sequence over an area of interest. This model allows for synthesizing textured views that correspond to the same viewpoints of a second image sequence. The generated views are photometrically matched and corrected against the corresponding frames from the second sequence. Standard change detection techniques are then applied to find areas of difference. Additionally, the paper shows that it is possible to detect false positives, resulting from non-rigid objects, by applying the same change detection method to the first sequence exclusively. The developed method was able to correctly find the changes between two challenging sequences of images from a coral reef taken one year apart and acquired with two different cameras

Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported

A Motion compensated filtering approach to remove sunlight flicker in shallow water images

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach

Planar homography: accuracy analysis and applications

Projective homography sits at the heart of many problems in image registration. In addition to many methods for estimating the homography parameters (R.I. Hartley and A. Zisserman, 2000), analytical expressions to assess the accuracy of the transformation parameters have been proposed (A. Criminisi et al., 1999). We show that these expressions provide less accurate bounds than those based on the earlier results of Weng et al. (1989). The discrepancy becomes more critical in applications involving the integration of frame-to-frame homographies and their uncertainties, as in the reconstruction of terrain mosaics and the camera trajectory from flyover imagery. We demonstrate these issues through selected examples

La Aplicación de estadísticas y de los SIG en el estudio de las construcciones monumentales prehistóricas de la Amazonía brasileña

Las estructuras monumentales prehistóricas construidas mediante zanjas continuas excavadas en el suelo de la Amazonia brasileña, son yacimientos que comprenden varias formas geométricas de diversos tamaños. Actualmente se conocen 291 yacimientos arqueológicos, la mayor parte de los cuales han sido mapeados por medio de imágenes de satélite. Estas construcciones prehistóricas fueron localizadas mediante la combinación de una serie de estrategias de prospección que incluyen el uso de imágenes satélites, sobrevuelos y otras tecnologías que posibilitaron su identificación. En un análisis de caracterización cuantitativa y morfológica y a través da estadísticas, obtuvimos como principales resultados que existe una gran dispersión de los datos correspondientes a su tamaño, siendo menor la variación para la profundidad, el valor medio de las áreas de los recintos con zanjas perimetrales es 17.490,6 m2 , a pesar de que el 40,3% mide menos de una hectárea (10.000 m ), la altitud media a la que se encuentran es de 194,4 metros y ésta es la variable que mejor correlación tiene con la posición geográfica. Con la ayuda de gvSIG, Sextante, GRASS y R, hemos tratado de caracterizar la ubicación de los yacimientos atendiendo a diferentes variables entre las que destacan la altitud relativa, la orientación, la distancia al curso de agua más próximo, la pendiente y la posición relativa en el territorio. La intención es intentar predecir en qué áreas, hoy en día cubiertas por la masa forestal, se pueden encontrar estructuras semejantes a las localizadas en las áreas abiertas. Este carácter predictivo de nuestras observaciones sería de vital importancia para poder definir futuras prospecciones en las áreas boscosas de la Amazonia.Para el futuro, no descartamos el aprovechamiento de datos LIDAR para intentar comprobar si las áreas designadas como potencialmente poseedoras de geoglifos efectivamente los poseen