Vegetation Detection Using Deep Learning and Conventional Methods

(Este artículo pertenece al Número Especial Avances Recientes en Clasificación de Cobertura Terrestre y Detección de Cambios en 2D y 3D)[EN] Land cover classification with the focus on chlorophyll-rich vegetation detection plays an important role in urban growth monitoring and planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional approaches usually apply the normalized difference vegetation index (NDVI) for vegetation detection. In this paper, we investigate the performance of deep learning and conventional methods for vegetation detection. Two deep learning methods, DeepLabV3+ and our customized convolutional neural network (CNN) were evaluated with respect to their detection performance when training and testing datasets originated from different geographical sites with different image resolutions. A novel object-based vegetation detection approach, which utilizes NDVI, computer vision, and machine learning (ML) techniques, is also proposed. The vegetation detection methods were applied to high-resolution airborne color images which consist of RGB and near-infrared (NIR) bands. RGB color images alone were also used with the two deep learning methods to examine their detection performances without the NIR band. The detection performances of the deep learning methods with respect to the object-based detection approach are discussed and sample images from the datasets are used for demonstrations.SIUS Department of Energy under grant # DE-SC001993

GEOMATICS AND CIVIL ENGINEERING INNOVATIVE RESEARCH ON HERITAGE: INTRODUCING THE “ENGINEER” PROJECT

This paper aims to introduce the concept and objectives of a recently supported European project entitled “Geomatics and Civil Engineering Innovative Research on Heritage”, in short ENGINEER. The ENGINEER project visions to enhance and extend inter- departmental multidisciplinary research activities of the Department of Civil Engineering & Geomatics of the Cyprus University of Technology through coordination and support actions as well as through targeted research activities with the support of European leading institutions. Project tasks aim to fill research multidisciplinary gaps, push, and extend knowledge into new and innovative fields dealing with the monitoring, digitization, visualization, and preservation of ancient monuments and cultural heritage sites, assisting their protection, promotion, and safeguarding

An Extensive Literature Review on Underwater Image Colour Correction

The topic of underwater (UW) image colour correction and restoration has gained significant scientific interest in the last couple of decades. There are a vast number of disciplines, from marine biology to archaeology, that can and need to utilise the true information of the UW environment. Based on that, a significant number of scientists have contributed to the topic of UW image colour correction and restoration. In this paper, we try to make an unbiased and extensive review of some of the most significant contributions from the last 15 years. After considering the optical properties of water, as well as light propagation and haze that is caused by it, the focus is on the different methods that exist in the literature. The criteria for which most of them were designed, as well as the quality evaluation used to measure their effectiveness, are underlined

An extensive literature review on underwater image colour correction

The topic of underwater (UW) image colour correction and restoration has gained significant scientific interest in the last couple of decades. There are a vast number of disciplines, from marine biology to archaeology, that can and need to utilise the true information of the UW environment. Based on that, a significant number of scientists have contributed to the topic of UW image colour correction and restoration. In this paper, we try to make an unbiased and extensive review of some of the most significant contributions from the last 15 years. After considering the optical properties of water, as well as light propagation and haze that is caused by it, the focus is on the different methods that exist in the literature. The criteria for which most of them were designed, as well as the quality evaluation used to measure their effectiveness, are underlined

An extensive literature review on underwater image colour correction

The topic of underwater (UW) image colour correction and restoration has gained significant scientific interest in the last couple of decades. There are a vast number of disciplines, from marine biology to archaeology, that can and need to utilise the true information of the UW environment. Based on that, a significant number of scientists have contributed to the topic of UW image colour correction and restoration. In this paper, we try to make an unbiased and extensive review of some of the most significant contributions from the last 15 years. After considering the optical properties of water, as well as light propagation and haze that is caused by it, the focus is on the different methods that exist in the literature. The criteria for which most of them were designed, as well as the quality evaluation used to measure their effectiveness, are underlined

Investigating influence of UAV flight patterns in multi-stereo view DSM accuracy

Current advancements on photogrammetric software along with affordability and wide spreading of Autonomous Unmanned Aerial Vehicles (AUAV), allow for rapid, timely and accurate 3D modelling and mapping of small to medium sized areas. Although the importance of flight patterns and large overlaps in aerial triangulation and Digital Surface Model (DSM) production from large format aerial cameras is well documented in literature, this is not the case for AUAV photography. This paper assess DSM accuracy of models created using different flight patterns and compares them against check points and Lidar data. Three UAV flights took place, with 70%-65% forward and side overlaps, with West-East (W-E), North-South (N-S) and Northwest-Southeast (NW-SE) directions. Blocks with different flight patterns were created and processed to create raster DSM with 0.25m ground pixel size using Multi View Stereo (MVS). Using Lidar data as reference, difference maps and statistics were calculated for each block, in order to evaluate their overall accuracy. The combined scenario performed slightly better that the rest. Because of their lower spatial resolution, Lidar data prove to be an inadequate reference data set, although according to their internal vertical precision they are superior to UAV DSM. Point cloud noise from MVS, is considerable in contrast to Lidar data. A Lidar data set from a lower flying platform such as helicopter might have been a better match to low flying UAV data

ENGINEER WP2 SS1 PhotogrammetryCloseRange NikonD780

This dataset was created during ENGINEER project activities and is accessible only upon user request and approval by the responsible national authority of Cyprus, namely the Department of Antiquities. The dataset pertains to close-range photogrammetry data acquired using a Nikon D780 camera

An adhoc UW image colour correction method and the impact on image feature matching & SfM-MVS 3D reconstruction

The problem of colour correction of underwater images concerns not only surveyors, who primarily use images for photogrammetric purposes, but also archaeologists, marine biologists, and many other experts of different disciplines whose aim is to study objects and lifeforms underwater. For this reason, this study aims to address and quantify the impact of an ad-hoc underwater image restoration algorithm regarding image feature matching and 3D reconstruction of the scene. The datasets used for the purpose of this study consist of the original and colour corrected images captured in two different sites located in Cyprus with different depths and different water conditions. The images were colour corrected following a simple mathematical model that utilizes the scene's geometry while considering also the absorption and backscattering of light in order to restore the missing colour information

ENGINEER WP2 SS1 UAV Autel

This dataset was created during ENGINEER project activities and is accessible only upon user request and approval by the responsible national authority of Cyprus, namely the Department of Antiquities. The dataset pertains to images acquired at the tombs of the kings using an Autel UAV

Software comparison for underwater archaeological photogrammetric applications

Presented at 27th CIPA International Symposium - Documenting the Past for a Better Future, Avila, Spain, 1-5 September, 2019This paper presents an investigation as to whether and how the selection of the SfM-MVS software affects the 3D reconstruction of submerged archaeological sites. Specifically, Agisoft Photoscan, VisualSFM, SURE, 3D Zephyr and Reality Capture software were used and evaluated according to their performance in 3D reconstruction using specific metrics over the reconstructed underwater scenes. It must be clarified that the scope of this study is not to evaluate specific algorithms or steps that the various software use, but to evaluate the final results and specifically the generated 3D point clouds. To address the above research issues, a dataset from the ancient shipwreck, laying at 45 meters below sea level, is used. The dataset is composed of 19 images having very small camera to object distance (1 meter), and 42 images with higher camera to object distance (3 meters) images. Using a common bundle adjustment for all 61 images, a reference point cloud resulted from the lower dataset is used to compare it with the point clouds of the higher dataset generated using the different photogrammetric packages. Following that, a comparison regarding the number of total points, cloud to cloud distances, surface roughness, surface density and a combined 3D metric was done to evaluate and see which one performed the best