FPGA-Based On-Board Geometric Calibration for Linear CCD Array Sensors

With increasing demands in real-time or near real-time remotely sensed imagery applications in such as military deployments, quick response to terrorist attacks and disaster rescue, the on-board geometric calibration problem has attracted the attention of many scientists in recent years. This paper presents an on-board geometric calibration method for linear CCD sensor arrays using FPGA chips. The proposed method mainly consists of four modules—Input Data, Coefficient Calculation, Adjustment Computation and Comparison—in which the parallel computations for building the observation equations and least squares adjustment, are implemented using FPGA chips, for which a decomposed matrix inversion method is presented. A Xilinx Virtex-7 FPGA VC707 chip is selected and the MOMS-2P data used for inflight geometric calibration from DLR (Köln, Germany), are employed for validation and analysis. The experimental results demonstrated that: (1) When the widths of floating-point data from 44-bit to 64-bit are adopted, the FPGA resources, including the utilizations of FF, LUT, memory LUT, I/O and DSP48, are consumed at a fast increasing rate; thus, a 50-bit data width is recommended for FPGA-based geometric calibration. (2) Increasing number of ground control points (GCPs) does not significantly consume the FPGA resources, six GCPs is therefore recommended for geometric calibration. (3) The FPGA-based geometric calibration can reach approximately 24 times faster speed than the PC-based one does. (4) The accuracy from the proposed FPGA-based method is almost similar to the one from the inflight calibration if the calibration model and GCPs number are the same

On Board Georeferencing Using FPGA-Based Optimized Second Order Polynomial Equation

For real-time monitoring of natural disasters, such as fire, volcano, flood, landslide, and coastal inundation, highly-accurate georeferenced remotely sensed imagery is needed. Georeferenced imagery can be fused with geographic spatial data sets to provide geographic coordinates and positing for regions of interest. This paper proposes an on-board georeferencing method for remotely sensed imagery, which contains five modules: input data, coordinate transformation, bilinear interpolation, and output data. The experimental results demonstrate multiple benefits of the proposed method: (1) the computation speed using the proposed algorithm is 8 times faster than that using PC computer; (2) the resources of the field programmable gate array (FPGA) can meet the requirements of design. In the coordinate transformation scheme, 250,656 LUTs, 499,268 registers, and 388 DSP48s are used. Furthermore, 27,218 LUTs, 45,823 registers, 456 RAM/FIFO, and 267 DSP48s are used in the bilinear interpolation module; (3) the values of root mean square errors (RMSEs) are less than one pixel, and the other statistics, such as maximum error, minimum error, and mean error are less than one pixel; (4) the gray values of the georeferenced image when implemented using FPGA have the same accuracy as those implemented using MATLAB and Visual studio (C++), and have a very close accuracy implemented using ENVI software; and (5) the on-chip power consumption is 0.659W. Therefore, it can be concluded that the proposed georeferencing method implemented using FPGA with second-order polynomial model and bilinear interpolation algorithm can achieve real-time geographic referencing for remotely sensed imagery

Transformation Model With Constraints for High Accuracy of 2D-3D Building Registration in Aerial Imagery

This paper proposes a novel rigorous transformation model for 2D-3D registration to address the difficult problem of obtaining a sufficient number of well-distributed ground control points (GCPs) in urban areas with tall buildings. The proposed model applies two types of geometric constraints, co-planarity and perpendicularity, to the conventional photogrammetric collinearity model. Both types of geometric information are directly obtained from geometric building structures, with which the geometric constraints are automatically created and combined into the conventional transformation model. A test field located in downtown Denver, Colorado, is used to evaluate the accuracy and reliability of the proposed method. The comparison analysis of the accuracy achieved by the proposed method and the conventional method is conducted. Experimental results demonstrated that: (1) the theoretical accuracy of the solved registration parameters can reach 0.47 pixels, whereas the other methods reach only 1.23 and 1.09 pixels; (2) the RMS values of 2D-3D registration achieved by the proposed model are only two pixels along the x and y directions, much smaller than the RMS values of the conventional model, which are approximately 10 pixels along the x and y directions. These results demonstrate that the proposed method is able to significantly improve the accuracy of 2D-3D registration with much fewer GCPs in urban areas with tall buildings

Development of an Aptamer-Conjugated Polyrotaxane-Based Biodegradable Magnetic Resonance Contrast Agent for Tumor-Targeted Imaging

Gadolinium-based magnetic resonance imaging (MRI) contrast agents with biodegradability, biosafety, and high efficiency are highly desirable for tumor diagnosis. Herein, a biodegradable, AS1411-conjugated, α-cyclodextrin polyrotaxane-based MRI contrast agent (AS1411-G2­(DTPA-Gd)-SS-PR) was developed for targeted imaging of cancer. The polyrotaxane-based contrast agent was achieved by the complexation of α-cyclodextrin (α-CD) and a linear poly­(ethylene glycol) (PEG) chain containing disulfide linkages at two terminals. The disulfides enable the dethreading of the polyrotaxane into excretable small units due to cleavage of the disulfide linkages by reducing agents such as intracellular glutathione (GSH). Furthermore, the second-generation lysine dendron conjugated with gadolinium chelates and AS1411, a G-quadruplex oligonucleotide that has high binding affinity to nucleolin generally presenting a high level on the surface of tumor cells, coupled to the α-CD via click chemistry. The longitudinal relaxivity of AS1411-G2­(DTPA-Gd)-SS-PR (11.7 mM–1 s–1) was two times higher than the clinically used Gd-DTPA (4.16 mM–1 s–1) at 0.5 T. The in vitro degradability was confirmed by incubating with 10 mM 1,4-dithiothreitol (DTT). Additionally, the cytotoxicity, histological assessment, and gadolinium retention studies showed that the prepared polyrotaxane-based contrast agent had a superior biocompatibility and was predominantly cleared renally without long-term accumulation toxicity. Importantly, AS1411-G2­(DTPA-Gd)-SS-PR displayed the enhanced performance in MRI of breast cancer cells in vitro as well as a subcutaneous breast tumor in vivo due to the targeting ability of the AS1411 aptamer. The enhanced performance was due to efficient multivalent interactions with tumor cells, producing faster accumulation and longer contrast imaging time at the tumor site. This work clearly confirms that the specially designed and fabricated α-CD-based polyrotaxane is a promising contrast agent with an excellent contrast imaging performance and biosafety for tumor MR imaging

De novo rational design of a freestanding, supercharged polypeptide, proton-conducting membrane

Proton translocation enables important processes in nature and man-made technologies. However, controlling proton conduction and fabrication of devices exploiting biomaterials remains a challenge. Even more difficult is the design of protein-based bulk materials without any functional starting scaffold for further optimization. Here, we show the rational design of proton-conducting, protein materials exceeding reported proteinaceous systems. The carboxylic acid-rich structures were evolved step by step by exploring various sequences from intrinsically disordered coils over supercharged nanobarrels to hierarchically spider β sheet containing protein-supercharged polypeptide chimeras. The latter material is characterized by interconnected β sheet nanodomains decorated on their surface by carboxylic acid groups, forming self-supportive membranes and allowing for proton conduction in the hydrated state. The membranes showed an extraordinary proton conductivity of 18.5 ± 5 mS/cm at RH = 90%, one magnitude higher than other protein devices. This design paradigm offers great potential for bioprotonic device fabrication interfacing artificial and biological systems

On-Board Detection and Matching of Feature Points

This paper presents a FPGA-based method for on-board detection and matching of the feature points. With the proposed method, a parallel processing model and a pipeline structure are presented to ensure a high frame rate at processing speed, but with a low power consumption. To save the FPGA resources and increase the processing speed, a model which combines the modified SURF detector and a BRIEF descriptor, is presented as well. Three pairs of images with different land coverages are used to evaluate the performance of FPGA-based implementation. The experiment results demonstrate that (1) when the image pairs with artificial features (such as buildings and roads), the performance of FPGA-based implementation is better than those image pairs with natural features (such as woods); (2) the proposed FPGA-based method is capable of ensuring the processing speed at a high frame rate, such as the speed of can achieve 304 fps under a 100 MHz clock frequency. The speedup of the proposed implementation is about 27 times higher than that when using the PC-based implementation

A New FPGA Architecture of FAST and BRIEF Algorithm for On-Board Corner Detection and Matching

Although some researchers have proposed the Field Programmable Gate Array (FPGA) architectures of Feature From Accelerated Segment Test (FAST) and Binary Robust Independent Elementary Features (BRIEF) algorithm, there is no consideration of image data storage in these traditional architectures that will result in no image data that can be reused by the follow-up algorithms. This paper proposes a new FPGA architecture that considers the reuse of sub-image data. In the proposed architecture, a remainder-based method is firstly designed for reading the sub-image, a FAST detector and a BRIEF descriptor are combined for corner detection and matching. Six pairs of satellite images with different textures, which are located in the Mentougou district, Beijing, China, are used to evaluate the performance of the proposed architecture. The Modelsim simulation results found that: (i) the proposed architecture is effective for sub-image reading from DDR3 at a minimum cost; (ii) the FPGA implementation is corrected and efficient for corner detection and matching, such as the average value of matching rate of natural areas and artificial areas are approximately 67% and 83%, respectively, which are close to PC’s and the processing speed by FPGA is approximately 31 and 2.5 times faster than those by PC processing and by GPU processing, respectively