Fusion of Urban TanDEM-X raw DEMs using variational models

Recently, a new global Digital Elevation Model (DEM) with pixel spacing of 0.4 arcseconds and relative height accuracy finer than 2m for flat areas (slopes 20%) was created through the TanDEM-X mission. One important step of the chain of global DEM generation is to mosaic and fuse multiple raw DEM tiles to reach the target height accuracy. Currently, Weighted Averaging (WA) is applied as a fast and simple method for TanDEM-X raw DEM fusion in which the weights are computed from height error maps delivered from the Interferometric TanDEM-X Processor (ITP). However, evaluations show that WA is not the perfect DEM fusion method for urban areas especially in confrontation with edges such as building outlines. The main focus of this paper is to investigate more advanced variational approaches such as TV-L1 and Huber models. Furthermore, we also assess the performance of variational models for fusing raw DEMs produced from data takes with different baseline configurations and height of ambiguities. The results illustrate the high efficiency of variational models for TanDEM-X raw DEM fusion in comparison to WA. Using variational models could improve the DEM quality by up to 2m particularly in inner-city subsets.Comment: This is the pre-acceptance version, to read the final version, please go to IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing on IEEE Xplor

The Approximate Capacity Region of the Gaussian Z-Interference Channel with Conferencing Encoders

A two-user Gaussian Z-Interference Channel (GZIC) is considered, in which encoders are connected through noiseless links with finite capacities. In this setting, prior to each transmission block the encoders communicate with each other over the cooperative links. The capacity region and the sum-capacity of the channel are characterized within 1.71 bits per user and 2 bits in total, respectively. It is also established that properly sharing the total limited cooperation capacity between the cooperative links may enhance the achievable region, even when compared to the case of unidirectional transmitter cooperation with infinite cooperation capacity. To obtain the results, genie-aided upper bounds on the sum-capacity and cut-set bounds on the individual rates are compared with the achievable rate region. In the interference-limited regime, the achievable scheme enjoys a simple type of Han-Kobayashi signaling, together with the zero-forcing, and basic relaying techniques. In the noise-limited regime, it is shown that treating interference as noise achieves the capacity region up to a single bit per user.Comment: 25 pages, 6 figures, submitted to IEEE Transactions on Information Theor

A Framework for SAR-Optical Stereogrammetry over Urban Areas

Currently, numerous remote sensing satellites provide a huge volume of diverse earth observation data. As these data show different features regarding resolution, accuracy, coverage, and spectral imaging ability, fusion techniques are required to integrate the different properties of each sensor and produce useful information. For example, synthetic aperture radar (SAR) data can be fused with optical imagery to produce 3D information using stereogrammetric methods. The main focus of this study is to investigate the possibility of applying a stereogrammetry pipeline to very-high-resolution (VHR) SAR-optical image pairs. For this purpose, the applicability of semi-global matching is investigated in this unconventional multi-sensor setting. To support the image matching by reducing the search space and accelerating the identification of correct, reliable matches, the possibility of establishing an epipolarity constraint for VHR SAR-optical image pairs is investigated as well. In addition, it is shown that the absolute geolocation accuracy of VHR optical imagery with respect to VHR SAR imagery such as provided by TerraSAR-X can be improved by a multi-sensor block adjustment formulation based on rational polynomial coefficients. Finally, the feasibility of generating point clouds with a median accuracy of about 2m is demonstrated and confirms the potential of 3D reconstruction from SAR-optical image pairs over urban areas.Comment: This is the pre-acceptance version, to read the final version, please go to ISPRS Journal of Photogrammetry and Remote Sensing on ScienceDirec

Nighttime Driver Behavior Prediction Using Taillight Signal Recognition via CNN-SVM Classifier

This paper aims to enhance the ability to predict nighttime driving behavior by identifying taillights of both human-driven and autonomous vehicles. The proposed model incorporates a customized detector designed to accurately detect front-vehicle taillights on the road. At the beginning of the detector, a learnable pre-processing block is implemented, which extracts deep features from input images and calculates the data rarity for each feature. In the next step, drawing inspiration from soft attention, a weighted binary mask is designed that guides the model to focus more on predetermined regions. This research utilizes Convolutional Neural Networks (CNNs) to extract distinguishing characteristics from these areas, then reduces dimensions using Principal Component Analysis (PCA). Finally, the Support Vector Machine (SVM) is used to predict the behavior of the vehicles. To train and evaluate the model, a large-scale dataset is collected from two types of dash-cams and Insta360 cameras from the rear view of Ford Motor Company vehicles. This dataset includes over 12k frames captured during both daytime and nighttime hours. To address the limited nighttime data, a unique pixel-wise image processing technique is implemented to convert daytime images into realistic night images. The findings from the experiments demonstrate that the proposed methodology can accurately categorize vehicle behavior with 92.14% accuracy, 97.38% specificity, 92.09% sensitivity, 92.10% F1-measure, and 0.895 Cohen's Kappa Statistic. Further details are available at https://github.com/DeepCar/Taillight_Recognition.Comment: 12 pages, 10 figure

Cooperative Protocols for Relay and Interference Channels with Half-Duplex Constraint

Enabling cooperation among nodes of a wireless network can significantly reduce the required transmit power as well as the induced intra-network interference. Due to the practical half-duplexity constraint of the cooperating nodes, they are prohibited to simultaneously transmit and receive data at the same time-frequency resource. The purpose of this dissertation is to illustrate the value of cooperation in such an environment. To understand how to cooperate efficiently, information theory is employed as a useful tool, which not only determines the fundamental limits of communication (i.e., capacity) over the considered network, but also provides insights into the design of a proper transmission scheme for that network. In this thesis, two simple but yet important types of wireless networks, namely Relay Channel, and Interference Channel are studied. In fact, these models constitute building blocks for larger networks. The first considered channel is a diamond-shaped relay channel consisting of a source, a destination, and two parallel relays. The second analyzed channel is an interference channel composed of two transmitter-receiver pairs with out-of-band transmitter cooperation, also referred to as conferencing encoders. While characterizing the capacity of these channels are difficult, a simpler and a more common approach is to find an achievable scheme for each channel that ensures a small gap from the capacity for all channel parameters. In chapter 2, the diamond relay channel is investigated in detail. Because of the half-duplex nature of the relays, each relay is either in transmit or receive mode, making four modes possible for the two-relay combination, specifically, 1) broadcast mode (both relays receive) 2,3) routing modes (one relay transmits, another receives) 4) multiple-access mode (both relays transmit). An appropriate scheduling ( i.e., timing over the modes) and transmission scheme based on the decode-and-forward strategy are proposed and shown to be able to achieve either the capacity for certain channel conditions or at most 3.6 bits below the capacity for general channel conditions. Particularly, by assuming each transmitter has a constant power constraint over all modes, a parameter Δ is defined, which captures some important features of the channel. It is proven that for Δ=0 the capacity of the channel can be attained by successive relaying, i.e., using modes 2 and 3 defined above in a successive manner. This strategy may have an infinite gap from the capacity of the channel when Δ≠0. To achieve rates as close as 0.71 bits to the capacity, it is shown that the cases of Δ>0 and Δ<0 should be treated differently. Using new upper bounds based on the dual problem of the linear program associated with the cut-set bounds, it is proven that the successive relaying strategy needs to be enhanced by an additional broadcast mode (mode 1), or multiple access mode (mode 4), for the cases of Δ0, respectively. Furthermore, it is established that under average power constraints the aforementioned strategies achieve rates as close as 3.6 bits to the capacity of the channel. In chapter 3, a two-user Gaussian Interference Channel (GIC) is considered, in which encoders are connected through noiseless links with finite capacities. The setup can be motivated by downlink cellular systems, where base stations are connected via infrastructure backhaul networks. In this setting, prior to each transmission block the encoders communicate with each other over the cooperative links. The capacity region and the sum-capacity of the channel are characterized within some constant number of bits for some special classes of symmetric and Z interference channels. It is also established that properly sharing the total limited cooperation capacity between the cooperative links may enhance the achievable region, even when compared to the case of unidirectional transmitter cooperation with infinite cooperation capacity. To obtain the results, genie-aided upper bounds on the sum-capacity and cut-set bounds on the individual rates are compared with the achievable rate region. The achievable scheme enjoys a simple type of Han-Kobayashi signaling, together with the zero-forcing, and basic relaying techniques