Stereo rectification of pushbroom satellite images by robustly estimating the fundamental matrix

ABSTRACT

Stereo rectification is one of the most important steps for stereo matching and subsequently for digital surface model generation from satellite stereo images. This study proposes a new framework to rectify two pushbroom images along the epipolar geometry in order to omit the vertical parallax between two images. Here, we assume the interior and relative parameters between the two pushbroom images are not known and the images can be taken at different dates. Traditional stereo rectification methods of pushbroom images require metadata such as rational polynomial coefficients (RPCs), parameters of physical sensor model or ground control points (GCPs). In this study, we develop an image-based framework for stereo rectification, which works without the need for such data. In the proposed framework, the correspondences are densely extracted by a tilling strategy, and then the fundamental matrix is robustly estimated by two geometric constraints. Both affine and projective fundamental matrices could be used for stereo rectification from pushbroom stereo images. The results on IRS P5, World view III, GeoEye and IKONOS stereo pairs as well as on multi-date stereo images demonstrate that the pushbroom images are rectified with sub-pixel accuracy.     

Photogrammetric exploitation of IKONOS imagery for mapping applications

The launch of IKONOS by Space Imaging opens a new era of high-resolution satellite imagery collection and mapping. The IKONOS satellite simultaneously acquires 1?m panchromatic and 4?m multi-spectral images in four bands that are suitable for high accuracy mapping applications. Space Imaging uses the rational function model (RFM), also known as rational polynomial camera model, instead of the physical IKONOS sensor model to communicate the imaging geometry. As revealed by recent studies from several researchers, the RFM retains the full capability of performing photogrammetric processing in absence of the physical sensor model. This paper presents some RFM-based processing methods and mapping applications developed for 3D feature extraction, orthorectification and RPC model refinement using IKONOS imagery. Comprehensive tests are performed to test the accuracy of 3D reconstruction and orthorectification and to validate the feasibility of the model refinement techniques.     

JX4C DPS中IKONOS立体像对的一体化处理

本文简要介绍了IKONOS遥感卫星系统及其立体影像数据的特点,给出了IKONOS影像立体模型的构建原理与方法,探讨了IKONOS影像的区域网平差方案,对少控制或无控制测图做了初步分析。随后,描述了JX4C数字摄影测量工作站中对IKONOS立体影像从数据预处理、单模型定向、区域网平差到区域DLG、DEM/DSM、DOM等测绘产品生产的一体化处理流程。文章最后指出,以IKONOS为代表的高分辨率遥感影像在测绘领域的广泛应用标志着卫星摄影测量与制图时代的开始。     

金字塔双层动态规划立体匹配算法

针对控制点修正的动态规划立体匹配算法存在控制点求取时阀长、实时性差的问题．提出一种金字塔双层动态规划立体匹配算法．采用金字塔算法求取低、商分辨率图像,然后分别在低、商分辨宰图像上求取候选控制点集和最终控制点集,并用最终控制点集修正商分辨率图像上的动态规划立体匹配．由干候选控制点集的求取在低分辨率图像上进行,算法用时大为减少．实验证明,此算法匹配率商、速度快．     

Geometric accuracy assessment of the orthorectification process from very high resolution satellite imagery for Common Agricultural Policy purposes

This study has, as its main aim, the assessment of different sensor models to achieve the best geometric accuracy in orthorectified imagery products obtained from IKONOS Geo Ortho Kit and QuickBird basic imagery. The final orthoimages are compared, both geometrically and visually, with the panchromatic orthophotos based on a photogrammetric flight with an approximate scale of 1 : 20 000, which are now used for the European Union Common Agricultural Policy in Andalusia (Spain). Two‐dimensional root mean square (RMS_2d) errors in independent check points are used as accuracy indicators. The ancillary data were generated by high accuracy methods: (1) check and ground control points (GCPs) were measured with a differential global positioning system and (2) an accurate digital elevation model was used for image orthorectification. Two sensor models were used to correct the satellite data: (1) a three‐dimensional (3D) rational function refined by the user with zero‐ (RPC0) or first‐(RPC1) order polynomial adjustment and (2) the 3D Toutin physical model (CCRS). For the IKONOS image, the best results in the final orthoimages (RMS_2d of about 1.15 m) were obtained when the RPC0 model was used. Neither a large number of GCPs (more than nine), nor a better distribution of them, improved the results obtained with the RPC0. For the QuickBird image, the CCRS model generated the best results (RMS_2d of about 1.04 m), although it was sensitive to the number and distribution of the GCPs used in its computation.     

Deriving relief of a coastal landscape with aerial video data

Coastal geomorphological research benefits from visualization of heights. Videography, a cheap, simple and flexible airborne remote sensing technique, was used for derivation of relief. A hand-held Hi 8 camera and a small aeroplane were used to collect video data of a 1300m X 320m strip of beach and foredune area on Ameland (the Netherlands). Simultaneously, the ground control points (GCPs) were measured with laser electronic distance measurement (EDM) equipment. A series of overlapping frames was grabbed, contrast-stretched and corrected for interlacing effects. The resulting images were processedwith software that has some photogrammetric capabilities, R-WEL's Desktop Mapping System (DMS). The images and the positions of the GCPs enabled computation of the camera orientation, and allowed for image rectification and stereo correlation. Stereo pairs form the basis for anaglyphs, which give a perception of height. In addition, the parallax in the stereo pairs allows a derivation of quantitative height information. Some of the derived height values are, however, incorrect. This was due to inaccuracies in the camera technology and the use of photogrammetric software that was not designed principally to process video imagery.     

Spatial accuracy of orthorectified IKONOS imagery and historical aerial photographs across five sites in China

High‐resolution (?1?m) satellite imagery and archival World War II era (WW2) aerial photographs are currently available to support high‐resolution long‐term change measurements at sites across China. A major limitation to these measurements is the spatial accuracy with which this imagery can be orthorectified and co‐registered. We orthorectified IKONOS 1?m resolution GEO‐format imagery and WW2 aerial photographs across five 100?km² rural sites in China with terrain ranging from flat to hilly to mountainous. Ground control points (GCPs) were collected uniformly across 100?km² IKONOS scenes using a differential Global Positioning Systems (GPS) field campaign. WW2 aerial photos were co‐registered to orthorectified IKONOS imagery using bundle block adjustment and rational function models. GCP precision, terrain relief and the number and distribution of GCPs significantly influenced image orthorectification accuracy. Root mean square errors (RMSEs) at GCPs for IKONOS imagery were <2.0?m (0.9–2.0?m) for all sites except the most heterogeneous site (Sichuan Province, 2.6?m), meeting 1:12?000 to 1:4800 US National Map Accuracy Standards and equalling IKONOS Precision and Pro format accuracy standards. RMSEs for WW2 aerial photos ranged from 0.2 to 3.5?m at GCPs and from 4.4 to 6.2?m at independent checkpoints (ICPs), meeting minimum requirements for high‐resolution change detection.     

Validation and comparison of different techniques for the derivation of digital elevation models and volcanic monitoring (Vulcano Island,Italy)

High accurate digital elevation models (DEM) acquired periodically over a volcanic area can be used for monitoring crustal deformations. Airborne stereoscopic photography is a powerful tool for the derivation of high resolution DEM, especially when combined with Global Positioning System (GPS). We analyse data acquired on Vulcano Island (Italy) to assess the performance of two photogrammetry methods for DEM generation. The first method is based on automatic digital processing of scanned airborne stereo images from a film camera (Wild RC20). In the second method digital stereo data from the multi-spectral High Resolution Stereo Camera-Airborne (HRSC-A) are used. Accuracy assessment through comparison with kinematic GPS height profiles shows that both DEMs have accuracy on the order of few decimetres. Direct comparison of the two DEMs on the La Fossa volcanic cone provides a standard deviation of the residuals of 78 cm. Residuals greater than two metres between the two DEMs acquired at one year interval are locally evidenced in unstable areas with uneven morphology. The application of photogrammetric DEMs is also discussed within a SAR interferometry study carried out on Vulcano Island to evaluate the potentialities of such techniques for ground deformation monitoring. Although accuracy better than 1 m or 2 m is not required for satellite SAR interferometry, we show how the precise photogrammetric DEMs could still significantly improve SAR interferograms of Vulcano Island.     

A mixed spaceborne sensor approach for surface modelling of an urban scene

Three-dimensional (3D) surface models are vital for sustainable urban management studies, and there is a nearly unlimited range of possible applications. Along- or across-track pairs from the same set of sensor imagery may not always be available or economical for a certain study area. Therefore, a photogrammetric approach is proposed in which a digital surface model (DSM) is extracted from a stereo pair of satellite images, acquired by different sensors. The results demonstrate that a mixed-sensor approach may offer a sound alternative to the more established along-track pairs. However, one should consider several criteria when selecting a suitable stereo pair. Two cloud-free acquisitions are selected from the IKONOS and QuickBird image archives, characterized by sufficient overlap and optimal stereo constellation in terms of complementarity of the azimuth and elevation angles. A densely built-up area in Istanbul, Turkey, covering 151 km² and with elevations ranging between sea level and approximately 160 m is presented as the test site. In addition to the general complexity of modelling the surface and elevation of an urban environment, multi-sensor image fusion has other particular difficulties. As the images are acquired from a different orbital pass, at a different date or instant and by a different sensor system, radiometric and geometric dissimilarities can occur, which may hamper the image-matching process. Strategies are presented for radiometric and geometric normalization of the multi-temporal and multi-sensor imagery and to deal with the differences in sensor characteristics. The accuracy of the generated surface model is assessed in comparison with 3D reference points, 3D rooftop vector data and surface models extracted from an along-track IKONOS stereo pair and an IKONOS triplet. When compared with a set of 35 reference GPS check points, the produced mixed-sensor model yields accuracies of 1.22, 1.53 and 2.96 m for the X, Y and Z coordinates, respectively, expressed in terms of root mean square errors (RMSEs). The results show that it is feasible to extract the DSM of a highly urbanized area from a mixed-sensor pair, with accuracies comparable with those observed from the DSM extracted from an along-track pair. Hence, the flexibility of reconstructing valuable elevation models is greatly increased by considering the mixed-sensor approach.     

Planar block adjustment and orthorectification of Chinese spaceborne SAR YG-5 imagery based on RPC

Yaogan-5(YG-5), launched in December 2008, is a Chinese high-resolution spaceborne synthetic aperture radar (SAR) satellite, with a ground resolution of 3 m. However, the direct geometric positioning accuracy of YG-5 slant range images is low and so is the mosaic accuracy of the orthoimages. To improve the geometric accuracy of YG-5 orthoimages, this article proposes a strategy to calculate the rational polynomial coefficients for each SAR image and then uses a planar block adjustment method to solve for the orientation research parameters of the SAR images to achieve the orthorectification while a auxiliary digital elevation model is necessary for height constraint. Compared with the traditional orthorectification method using a single image, this strategy can ensure both uniformity in positioning accuracy of orthorectified images and high mosaic accuracy of adjacent orthoimages based on a small number of ground control points (GCPs). Tests using Chinese YG-5 satellite data over Xi’an and Xianning, China show that, using four GCPs positioned in the four corners of the test area, we can achieve independent check point plane accuracies better than ±4 m after the planar block adjustment. Finally, this article demonstrated that seamless mosaic geometry levels can be attained after the block orthorectification.     

Detection of attitude constant error and in-orbit calibration for the three-line CCD sensor of the ZY-3 satellite

In-orbit calibration of satellite optical sensors is of crucial importance for improving the accuracy and stability of high-resolution satellite stereo mapping and positioning. For the in-orbit calibration of Ziyuan 3 (ZY-3), the first Chinese three-line stereo mapping satellite, a rigorous imaging geometric model of the three-line sensors is established and the internal systematic error is modelled during analysis of the satellite structure and charge-coupled device (CCD) array. To improve the accuracy and stability of the in-orbit calibration, a new trajectory model, piece-point with weight polynomial model, is used and compared with models in current use. In addition, an attitude constant error model is constructed and applied to reduce attitude errors and provide a more accurate initial attitude value, thus increasing the accuracy and stability of the in-orbit calibration. In addition, ground control point (GCP) stripes, established by partitioning GCPs into stripes, are proposed and used to eliminate random errors during in-orbit calibration. Finally, in-orbit calibration is performed for single and multiple sensors and the result of the calibration is assessed using GCPs and checkpoints. Based on the calibration result, variations of the three-line CCD array on ZY-3 are calculated and analysed in the along- and cross-track directions.     

Surface motion of mountain glaciers derived from satellite optical imagery

A complete and detailed map of the ice-velocity field on mountain glaciers is obtained by cross-correlating SPOT5 optical images. This approach offers an alternative to SAR interferometry, because no present or planned RADAR satellite mission provides data with a temporal separation short enough to derive the displacements of glaciers. The methodology presented in this study does not require ground control points (GCPs). The key step is a precise relative orientation of the two images obtained by adjusting the stereo model of one “slave”' image assuming that the other “master” image is well georeferenced. It is performed with numerous precisely-located homologous points extracted automatically. The strong ablation occurring during summer time on the glaciers requires a correction to obtain unbiased displacements. The accuracy of our measurement is assessed based on a comparison with nearly simultaneous differential GPS surveys performed on two glaciers of the Mont Blanc area (Alps). If the images have similar incidence angles and correlate well, the accuracy is on the order of 0.5 m, or 1/5 of the pixel size. Similar results are also obtained without GCPs. An acceleration event, observed in early August for the Mer de Glace glacier, is interpreted in term of an increase in basal sliding. Our methodology, applied to SPOT5 images, can potentially be used to derive the displacements of the Earth's surface caused by landslides, earthquakes, and volcanoes.     

Digital elevation model (DEM) generation and accuracy assessment from ASTER stereo data

Digital elevation models (DEM) are the indispensable quantitative environmental variable in most of the research studies in remote sensing. The improvement of sensor and satellite imaging technologies enabled the researchers to generate DEM using remotely sensed data. These data can be started to use as not only the two-dimensional (2-D) but also three-dimensional (3-D) information sources with usage of the DEM. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is one of the sensor systems capable of DEM generation and during the study, ASTER level 1A (L1A) data were used. Due to presence of many geological features and different landcover types, the test site is selected as the watershed of Asarsuyu River, located in north-western Anatolia in between Duzce and Bolu plains. The aim of this study is to check the best effort of 15 m spatial resolution DEM generation from ASTER L1A data by collecting different numbers of ground control points (GCP) (30, 45, and 60) and tie points (TP). During the study, three different techniques—spatial correlation, image differencing and profiling—were used for both planimetric and vertical accuracy assessment. The obtained results from both of the techniques show that the accuracy of the DEM increases by increasing the number of GCP. However, there is an only slight difference between the result of 45 GCPs and 60 GCPs.     

The impact of number and spatial distribution of GCPs on the positional accuracy of geospatial products derived from low-cost UASs

ABSTRACT

Currently, orthophotos and Digital Terrain Models (DTMs) are commonly being generated from low-cost consumer-grade Unmanned Aerial Systems (UASs) using well-known workflows based on photogrammetric and structure-from-motion methods. To achieve high accuracy positioning standards Ground Control Points (GCPs) have to be used in the workflow. In this paper, we assess the impact of number and spatial distribution of GCPs on the positional accuracy of these two geospatial products. By using 3 well-known mapping accuracy standards and 170 checkpoints, the planimetric and altimetric accuracy is assessed for 13 cases of GCPs configuration. The results show that in general, the UAS workflow presents a better accuracy in planimetry than in altimetry. In addition, the application of the mapping standards shows that the two products are suitable for GIS and mapping applications requiring spatial details equivalent to scales less than or equal 1:3000. We also conclude that the insertion of GCPs in the central part of the block does not contribute significantly to an increase in the planimetric accuracy of the geospatial products. Finally, for the proposed minimum photogrammetric overlaps (70% and 35%), the ideal GCP distribution consists of a uniform distribution of GCPs. First, on the central part the block with a horizontal separation of 3 to 4 ground base units for the altimetric component. Second, on the periphery of the block with a separation of 7 to 8 ground base units for the planimetric component.     

Block bundle adjustment of Ikonos in-track images

This letter presents a block bundle adjustment process applied to four Ikonos Geo-product in-track images with few ground control points (GCPs) over a high mountainous area of Venezuela. Various configurations of block bundle adjustment (1-4 images and different GCPs) were evaluated with independent check points. Whatever the number of images, the block bundle adjustment results were consistent with planimetric errors of about @ 5 m to - 7 m. Part of this error was due to the error of the ground data. The evaluation of the final ortho-mosaic with 1:1000 vector lines gives an approximation of relative and absolute errors to be - 2 m and - 3 m to - 4 m with maximum errors of - 6 m and - 10 m, respectively.     

Combining Structure from Motion and close-range stereo photogrammetry to obtain scaled gravel bar DEMs

ABSTRACT

Digital elevation models (DEMs) have been increasingly applied in topographic studies in areas such as physical geography and hydraulic engineering. Several methods have been proposed to reconstruct DEMs, including classic close-range stereo photogrammetry and the more novel Structure from Motion (SfM) methodology. Past published studies tend to apply SfM to large-scale environmental processes, whilst classic close-range stereophotogrammetry is focusing on detailed small-scale applications. However, SfM requires multiple ground control points (GCPs) to allow for proper DEM scaling. The larger the study area, the more GCPs are required, resulting in increased operational complexity and time-consuming application of SfM. As the accuracy of the DEM depends on the equipment used to measure GCPs, this can also result in a cost-expensive operation. In the present study, we introduce a combined SfM and close-range stereo photogrammetry application, with the close-range stereo photogrammetry results serving as a control for providing scale, thus eliminating the need for traditional GCPs. To validate our methodology, we studied a 40 m long gravel bar. We used GoPro Hero 3 cameras for SfM measurements and replaced GCPs by DEMs obtained through close-range stereo photogrammetry with a Nikon D5100 camera pair in stereo. In addition to using photo-mode frames, we also studied the quality of DEMs obtained with GoPro Hero 3 video-mode frames, and show how the DEM quality is reduced due to the smaller image format, hence coarser point cloud spacing, which eventually results in a convex curvature when image overlap was increased. Our results show that it is possible to collect high-quality topographic surface data by only using cameras, and alleviate the need for GCPs. The proposed workflow reduces the complexity, time, and resource demands associated with deploying GCPs and necessary independent geo-referencing, ensuring that digital photogrammetry will continue to gain popularity for field surveying.     

Global DEMs to tackle RPC biases and the overfitting phenomenon in high-resolution satellite imagery

ABSTRACT

The overfitting phenomenon and rational polynomial coefficients (RPCs) biases are two crucial issues that degrade the accuracy of geospatial products derived from high-resolution satellite images. The overfitting phenomenon is caused by both a large number of RPCs and strong correlations among them. The RPC biases arise from uncertainties in the global positioning system receivers and inertial measurement units. In this article, an innovative framework based on the genetic algorithm (GA) and the least squares (LS) algorithm, called GALS, is proposed to overcome these problems simultaneously. In this method, the GA is applied to select the optimum RPCs, while the LS algorithm is used to estimate the values of the optimally selected RPCs. The GALS method requires various sets of well-distributed ground control points (GCPs). To tackle the problem of GCP collection, we generated a large number of digital elevation model (DEM)-derived GCPs (DEMGCPs), using a global DEM (GDEM) and vendor-provided RPCs, refined by only one GCP. To evaluate the performance of this framework, four IRS-P5 data sets were used. The GALS is compared to two competing methods, L1-norm-regularized LS and ridge estimation by considering two scenarios using 50 GCPs and the DEMGCPs. The results demonstrate the superiority of GALS in both scenarios. Furthermore, GALS using DEMGCPs led to far more accurate and stable results when compared to GALS using GCPs. Compared to the vendor-provided RPCs, the results of the GALS using DEMGCPs also indicate a major improvement, single-pixel or subpixel accuracy with around 15 RPCs, and only 1 GCP, in both accuracy and reliability of georeferencing for all IRS-P5 data sets.     

Post-launch analysis,calibration, and validation of CCD line of sight for a space-borne push-broom electro-optical sensor using a global image data set

This article describes a technique which estimates line-of-sight (LOS) parameters of each CCD array in a high-resolution electro-optical sensor on board a satellite using statistical information which is extracted automatically from a large number of real images acquired after launch. First, the focal length of panchromatic (PAN) CCD arrays is estimated by using thousands of ground control points (GCPs) converted to raw image space. Second, a model is introduced for deriving LOS parameters for multispectral (MS) CCD arrays in one focal plane assembly (FPA) such as the focal lengths and the first/last detector cell positions from automatically matched band-to-band (B2B) tie-points. Finally, the LOS parameters of all arrays in one FPA are updated using automatically matched tie-points in the overlap zone (OZ) in order to represent the geometrical relationship between the CCD arrays with the same spectral band in two FPAs. The proposed technique was applied to the calibration of a ground segment image processor for a currently operating high-resolution imaging satellite during its initial commissioning phase. This article describes the accuracy and robustness of the LOS parameters estimated by the proposed technique by using more than one hundred images covering full geographical locations and off-nadir tilt angle ranges.     

Block adjustment with airbrone SAR very high-resolution images using trajectory constraints

For mapping a large area with airbrone synthetic aperture radar (SAR), very high-resolution (VHR) images using radargrammtry, block adjustment, where strips and blocks of images are processed together, is a preferred method for geometric processing with the advantage of reducing the needed number of ground control points (GCPs). However, the weak intersection geometry between adjacent images from the same strip conflicts with the solvability of the iterative least squares adjustment. In order to overcome this challenge, this article focuses on block adjustment with airbrone SAR VHR images using r-D model combined with trajectory constraints from azimuth tie points (ATPs). Initially, r-D model is briefly introduced. Then, the trajectory constraint equations are proposed and formulated with ATPs. Finally, an improved solution method is applied to increase the computational efficiency of the least squares process. Experiments are carried out using Chinese airbrone SAR VHR images over Shanxi Yanliang, China. The results show that the proposed method can effectively improve the accuracy of block adjustment in both range and elevation direction, with the root mean square error reduced from 0.440 to 0.253 m in range direction and from 0.501 to 0.256 m in elevation direction, respectively. The effects of the distribution and number of GCPs are also investigated, based on which some rules-of-thumb are derived.     

Automatic registration of SeaWiFS and AVHRR imagery

An automatic approach for integrating images from multitemporal and multisensor remote sensing is outlined based on coastlines derived from satellite images. One point on a coastline is taken as a candidate point of ground control points (GCPs). A correlation-relaxation (CR) technique is used to search for the corresponding point in the second image. A decision rule is used to guarantee the correctness of GCPs which are used to compute a polynomial equation for registering two images. The relationship between the accuracy of registration and the number of GCPs indicates that a large number of GCPs will lead to more accurate image registration. The correctness of GCPs can also improve the accuracy of geometric registration. The approach can be used particularly well to register images of coastal areas. Examples are given for registration of SeaWiFS and AVHRR imagery.