Seamless Mosaic Research Articles

A Global Adjustment Method for Photogrammetric Processing of Chang’E-2 Stereo Images

The Chang’E-2 (CE2) lunar orbiter was the second robotic orbiter of the Chinese Lunar Exploration Program, as well as the pioneer robotic orbiter in the soft landing project in the second phase of the program. It used a two-line stereo camera to acquire stereo images with global coverage at a resolution of 7 m. The stereo images have a large potential for producing the best lunar topographic map. However, errors and uncertainties in the interior orientation (IO) and exterior orientation (EO) parameters of the camera seriously affected the accuracy of the global topographic mapping. In this paper, a global adjustment method is proposed to eliminate the effects of these errors. The error models are represented by a Chebyshev polynomial. The polynomial coefficients were estimated as unknowns using five lunar laser ranging retroreflector (LRRR) points as ground control points in the adjustment. The experimental results show that the planimetric and height deviations between the neighboring strips were 5 and 2 m (less than 1 pixel), respectively, which were decreased by 32.6 and 31.5 times, respectively, relative to those derived from the original EO parameters. The large inconsistencies in the CE2 trajectory data were significantly reduced after the adjustment. In comparison with the LRRR positions, the planimetric and height errors ranged from 21 to 97 m and −19 to 10 m, respectively. A new seamless mosaic and high precision absolute position topographic map has been generated using this method.

Edge Fusion Algorithm for Orthogonal Projection of Multiple Overlapping Regions

Stereo projection display technology has become a hot topic in recent years. A edge fusion technology for multiple projection images with multiple overlapping areas is proposed. An edge fusion method is proposed, which can be used for edge fusion of multiple overlapping areas in irregular fusion areas, eliminate the bright band caused by overlapping projection and realize multi-channel seamless Mosaic display. The practical application shows that this method can make the multi-projector display system with multiple planar and different shape and multiple overlapping areas project a seamless vision.

Computational methods for stitching, alignment, and artifact correction of serial section data.

Imaging large samples at the resolution offered by electron microscopy is typically achieved by sequentially recording overlapping tiles that are later combined to seamless mosaics. Mosaics of serial sections are aligned to reconstruct three-dimensional volumes. To achieve this, image distortions and artifacts as introduced during sample preparation or imaging need to be removed. In this chapter, we will discuss typical sources of artifacts and distortion, and we will learn how to use the open source software TrakEM2 to correct them.

Radiometric homogenisation of aerial images by calibrating with satellite data

ABSTRACTThe use of very high resolution (VHR) aerial imagery for quantitative remote sensing has been limited by unwanted radiometric variation over temporal and spatial extents. In this paper we propose a simple yet effective technique for the radiometric homogenisation of the digital numbers of aerial images. The technique requires a collocated and concurrent, well-calibrated satellite image as surface reflectance reference to which the aerial images are calibrated. The bands of the reference satellite sensor should be spectrally similar to those of the aerial sensor. Using radiative transfer theory, we show that a spatially varying local linear model can be used to approximate the relationship between the surface reflectance of the reference image and the digital numbers of the aerial images. The model parameters for each satellite pixel location are estimated using least squares regression inside a small sliding window. The technique was applied to a set of aerial images captured over multiple days with an Intergraph Digital Mapping Camera (DMC) system. A near-concurrent Moderate Resolution Imaging Spectroradiometer (MODIS) nadir bidirectional reflectance distribution function (BRDF) adjusted reflectance image was used as the reflectance reference dataset. The resulting DMC mosaic was compared to a near-concurrent Satellite Pour l’Observation de la Terre (SPOT) 5 reflectance image of a portion of the same area, omitting the blue channel from the DMC mosaic due to its absence in the SPOT 5 data. The mean absolute reflectance difference was found to be 3.43% and the mean coefficient of determination (R2) over the bands was 0.84. The technique allows the production of seamless mosaics corrected for coarse scale atmospheric and BRDF effects and does not require the manual acquisition (or provision) of ground reflectance references. The accuracy of corrections is limited by the resolution of the reference image, which is generally significantly coarser than VHR imagery. The method cannot correct for small scale BRDF or other variations not captured at the reference resolution. Nevertheless, results show a significant improvement in homogeneity and correlation with SPOT 5 reflectance.

Evaluating Landscape Degradation Along Climatic Gradients During the 1930s Dust Bowl Drought From Panchromatic Historical Aerial Photographs, United States Great Plains

The U.S. Great Plains (USGP) are some of the most productive rangelands globally and a significant carbon sink for the atmosphere, but grassland response to precipitation is highly variable and poorly constrained over time and space. There is a rich historical aerial photographic record of the USGP which provides an unparalleled view of past landscapes and allows for evaluation of surficial response to drought beyond the satellite record, such as during the 1930s Dust Bowl Drought (DBD). This study classified the extent and loci of surficial denudation from seamless mosaics of radiometrically-corrected and georectified digitized aerial negatives acquired in the late 1930s from six counties distributed across USGP ecoregions. The dominant sources of degradation found for sites east of the 100th meridian are cultivated fields and fluvial deposits, associated with woody vegetation response to water availability in uncultivated areas. For sites to the west, denuded surfaces are predominantly eolian sandsheets and dunes, correlated with intensity of drought conditions and reduced plant diversity. Discrete spatial signatures of the drought are observed not only within the classically recognized southern Dust Bowl area, but also in the northern and central plains. Statistical analyses of site variability suggest landscape response to the DBD is most strongly influenced by the arid–humid divide and severity of precipitation and temperature anomalies. With a projected increase 21st century aridity, eolian processes cascading across western grasslands, like during the Dust Bowl, may significantly impact future dust particle emission and land and carbon storage management.

Instant 3D photography

We present an algorithm for constructing 3D panoramas from a sequence of aligned color-and-depth image pairs. Such sequences can be conveniently captured using dual lens cell phone cameras that reconstruct depth maps from synchronized stereo image capture. Due to the small baseline and resulting triangulation error the depth maps are considerably degraded and contain low-frequency error, which prevents alignment using simple global transformations. We propose a novel optimization that jointly estimates the camera poses as well as spatially-varying adjustment maps that are applied to deform the depth maps and bring them into good alignment. When fusing the aligned images into a seamless mosaic we utilize a carefully designed data term and the high quality of our depth alignment to achieve two orders of magnitude speedup w.r.t. previous solutions that rely on discrete optimization by removing the need for label smoothness optimization. Our algorithm processes about one input image per second, resulting in an end-to-end runtime of about one minute for mid-sized panoramas. The final 3D panoramas are highly detailed and can be viewed with binocular and head motion parallax in VR.

Colour Vignetting Correction for Microscopy Image Mosaics Used for Quantitative Analyses.

Image mosaicing permits achieving one high-resolution image, extending the visible area of the sample while keeping the same resolution. However, intensity inhomogeneity of the stitched images can alter measurements and the right perception of the original sample. The problem can be solved by flat-field correcting the images through the vignetting function. Vignetting correction has been widely addressed for grey-level images, but not for colour ones. In this work, a practical solution for the colour vignetting correction in microscopy, also facing the problem of saturated pixels, is described. In order to assess the quality of the proposed approach, five different tonal correction approaches were quantitatively compared using state-of-the-art metrics and seven pairs of partially overlapping images of seven different samples. The results obtained proved that the proposed approach allows obtaining high quality colour flat-field corrected images and seamless mosaics without employing any blending adjustment. In order to give the opportunity to easily obtain seamless mosaics ready for quantitative analysis, the described vignetting correction method has been implemented in an upgraded release of MicroMos (version 3.0), an open-source software specifically designed to automatically obtain mosaics of partially overlapped images.

The Poetic Innovation in the Poetry of Ahmed Hijazi

The contemporary Egyptian poet, critic, editor and convener of many conferences and cultural committees Ahmed Abdul Mu'tiHijazirepresents a case of dispute and discussion thanks to the selection of the material of his poems as well as the distinct shape and innovative aspects of his verse. As will be shown in the following pages,Hijazi's version of poetic modernism is devoid of mythology, intersexuality and deliberate obfuscation or self-indulgence. Every word in his poem is aligned in a seamless mosaic that eventually succeeds in conveying the poet's message in clear and lucid but highly suggestive discourse. It is this particular side of his verse that will be highlighted in the present study.

NSCT‐based fusion method for forward‐looking sonar image mosaic

To generate a seamless mosaic of a forward-looking sonar (FLS) video sequence, this study proposes a novel fusion method for FLS image mosaic, which includes two main steps from coarse to fine. In the coarse fusion step, the source images are first decomposed into multi-scale sub-bands using the non-subsampled contourlet transform (NSCT), then the sub-bands of the source images are merged, based on the Gabor energy and the local contrast for low and high frequency sub-bands, respectively, to generate the fused sub-bands which are used to produce the fused image by inverse NSCT. In the fine fusion step, a decision map is used to choose the pixels of the fine fused image from the coarsely fused image or one of the source images. This decision map is first constructed by measuring the similarity of the coarsely fused image to the source images, and then processed by a morphological post-processing technique to ensure its continuity and smoothness. Extensive experiments on FLS image fusion and mosaic have been conducted to demonstrate the effectiveness and the superiority of the proposed technique using both a subjective evaluation and objective metrics.

Optimal seamline detection in dynamic scenes via graph cuts for image mosaicking

In this paper, we present a novel method for creating a seamless mosaic from a set of geometrically aligned images captured from the scene with dynamic objects at different times. The artifacts caused by dynamic objects and geometric misalignments can be effectively concealed in our proposed seamline detection algorithm. In addition, we simultaneously compensate the image regions of dynamic objects based on the optimal seamline detection in the graph cuts energy minimization framework and create the mosaic with a relatively clean background. To ensure the high quality of the optimal seamline, the energy functions adopted in graph cuts combine the pixel-level similarities of image characteristics, including intensity and gradient, and the texture complexity. To successfully compensate the image regions covered by dynamic objects for creating a mosaic with a relatively clean background, we initially detect them in overlap regions between images based on pixel-level and region-level similarities, then refine them based on segments, and determine their image source in probability based on contour matching. We finally integrate all of these into the energy minimization framework to detect optimal seamlines. Experimental results on different dynamic scenes demonstrate that our proposed method is capable of generating high-quality mosaics with relatively clean backgrounds based on the detected optimal seamlines.

Stitching images of dual-cameras onboard satellite

The way of installing dual-cameras on one satellite is adopted to further enlarge the imaging swath, thereby improving the efficiency of data capturing. In this case, stitching images of dual-cameras with high precision is a key step in the practical application. Due to the inadequate overlapping area of dual-cameras, stitching their images by classic methods may cause internal accuracy loss of the mosaic image. The reason is that classic methods estimate the geometric transformation of dual-cameras merely by a few unevenly distributed precise tie points in overlapping area of dual-cameras, which is similar to the case of using unevenly distributed ground control points (GCPs) in block adjustment. This paper proposed a new method to precisely stitch images of dual cameras without losing internal accuracy. First, a model was built to recover the relative geometric relation of dual-cameras and eliminate Charge-Coupled Device (CCD) distortions of each camera, then a virtual camera model depending on the calibrated geometric relation was adopted to achieve a seamless mosaic image. The panchromatic images of camera A and camera B onboard Yaogan-24 were collected as the experimental data. Experiment results show that the calibration accuracies of dual-cameras are better than 0.3 pixels, and the stitching accuracies can reach the sub-pixel level, ranging from 0.3 to 0.5 pixels. On the other hand, the positioning accuracies with GCPs of the mosaic image and of individual camera are better than 0.6 pixels and 0.5 pixels respectively, so the internal accuracy loss of the mosaic image only reaches 0.1 pixels, which can be neglected. This demonstrates that the proposed method can achieve seamless mosaic images without losing internal accuracy.

A Physically Based Two-Dimensional Seamless Reflectivity Mosaic for Radar QPE in the MRMS System

Abstract The U.S. Weather Surveillance Radar-1988 Doppler (WSR-88D) network has provided meteorologists and hydrologists with quantitative precipitation observations at an unprecedented high spatial–temporal resolution since its deployment in the mid-1990s. Since each single radar can only cover a maximum range of 460 km, a mosaic of multiple-radar observations is needed to generate any national-scale products. The Multi-Radar Multi-Sensor (MRMS) system utilizes a physically based two-dimensional mosaicking algorithm of the WSR-88D data to generate seamless national quantitative precipitation estimation (QPE) products. For areas covered by multiple radars, the mosaicking scheme first determines if precipitation is present by checking the lowest-altitude observation. If the lowest observed radar data indicate no precipitation, then the mosaicked value is set to no precipitation. Otherwise, a weighted mean of multiple-radar observations is taken as the mosaicked value. The weighting function is based on multiple factors, including the distance from the radar and the height of the observation with respect to the melting layer. The mosaic algorithm uses the physically lowest radar observations with no/little blockage while maintaining a spatial continuity in the mosaicked field. The performance of the MRMS seamless radar mosaic algorithm was examined for various precipitation events of different characteristics. The results of these case evaluations are presented in this paper.

Panoramic Mosaics from Chang’E-3 PCAM Images at Point A

This paper presents a unique approach for panoramic mosaics based on Moon surface images from the Chang’E-3 (CE-3) mission, with consideration of the exposure time and external illumination changes in CE-3 Panoramic Camera (PCAM) imaging. The engineering implementation involves algorithms of image feature points extraction by using Speed-Up Robust Features (SURF), and a newly defined measure is used to obtain the corresponding points in feature matching. Then, the transformation matrix is calculated and optimized between adjacent images by the Levenberg–Marquardt algorithm. Finally, an image is reconstructed by using a fade-in-fade-out method based on linear interpolation to achieve a seamless mosaic. The developed algorithm has been tested with CE-3 PCAM images at Point A (one of the rover sites where the rover is separated from the lander). This approach has produced accurate mosaics from CE-3 PCAM images, as is indicated by the value of the Peak Signal to Noise Ratio (PSNR), which is greater than 31 dB between the overlapped region of the images before and after fusion.

MOSAICKING MEXICO - THE BIG PICTURE OF BIG DATA

The project presented in this article is to create a completely seamless and cloud-free mosaic of Mexico at a resolution of 5m, using approximately 4,500 RapidEye images. To complete this project in a timely manner and with limited operators, a number of processing architectures were required to handle a data volume of 12 terabytes. This paper will discuss the different operations realized to complete this project, which include, preprocessing, mosaic generation and post mosaic editing. Prior to mosaic generation, it was necessary to filter the 50,000 RapidEye images captured over Mexico between 2011 and 2014 to identify the top candidate images, based on season and cloud cover. Upon selecting the top candidate images, PCI Geomatics’ GXL system was used to reproject, color balance and generate seamlines for the output 1TB+ mosaic. This paper will also discuss innovative techniques used by the GXL for color balancing large volumes of imagery with substantial radiometric differences. Furthermore, post-mosaicking steps, such as, exposure correction, cloud and cloud shadow elimination will be presented.

RADIOMETRIC NORMALIZATION OF LARGE AIRBORNE IMAGE DATA SETS ACQUIRED BY DIFFERENT SENSOR TYPES

Generating seamless mosaics of aerial images is a particularly challenging task when the mosaic comprises a large number of im-ages, collected over longer periods of time and with different sensors under varying imaging conditions. Such large mosaics typically consist of very heterogeneous image data, both spatially (different terrain types and atmosphere) and temporally (unstable atmo-spheric properties and even changes in land coverage). <br><br> We present a new radiometric normalization or, respectively, radiometric aerial triangulation approach that takes advantage of our knowledge about each sensor’s properties. The current implementation supports medium and large format airborne imaging sensors of the Leica Geosystems family, namely the ADS line-scanner as well as DMC and RCD frame sensors. A hierarchical modelling – with parameters for the overall mosaic, the sensor type, different flight sessions, strips and individual images – allows for adaptation to each sensor’s geometric and radiometric properties. Additional parameters at different hierarchy levels can compensate radiome-tric differences of various origins to compensate for shortcomings of the preceding radiometric sensor calibration as well as BRDF and atmospheric corrections. The final, relative normalization is based on radiometric tie points in overlapping images, absolute radiometric control points and image statistics. It is computed in a global least squares adjustment for the entire mosaic by altering each image’s histogram using a location-dependent mathematical model. This model involves contrast and brightness corrections at radiometric fix points with bilinear interpolation for corrections in-between. The distribution of the radiometry fixes is adaptive to each image and generally increases with image size, hence enabling optimal local adaptation even for very long image strips as typi-cally captured by a line-scanner sensor. <br><br> The normalization approach is implemented in HxMap software. It has been successfully applied to large sets of heterogeneous imagery, including the adjustment of original sensor images prior to quality control and further processing as well as radiometric adjustment for ortho-image mosaic generation.

RADIOMETRIC NORMALIZATION OF LARGE AIRBORNE IMAGE DATA SETS ACQUIRED BY DIFFERENT SENSOR TYPES

Abstract. Generating seamless mosaics of aerial images is a particularly challenging task when the mosaic comprises a large number of im-ages, collected over longer periods of time and with different sensors under varying imaging conditions. Such large mosaics typically consist of very heterogeneous image data, both spatially (different terrain types and atmosphere) and temporally (unstable atmo-spheric properties and even changes in land coverage). We present a new radiometric normalization or, respectively, radiometric aerial triangulation approach that takes advantage of our knowledge about each sensor’s properties. The current implementation supports medium and large format airborne imaging sensors of the Leica Geosystems family, namely the ADS line-scanner as well as DMC and RCD frame sensors. A hierarchical modelling – with parameters for the overall mosaic, the sensor type, different flight sessions, strips and individual images – allows for adaptation to each sensor’s geometric and radiometric properties. Additional parameters at different hierarchy levels can compensate radiome-tric differences of various origins to compensate for shortcomings of the preceding radiometric sensor calibration as well as BRDF and atmospheric corrections. The final, relative normalization is based on radiometric tie points in overlapping images, absolute radiometric control points and image statistics. It is computed in a global least squares adjustment for the entire mosaic by altering each image’s histogram using a location-dependent mathematical model. This model involves contrast and brightness corrections at radiometric fix points with bilinear interpolation for corrections in-between. The distribution of the radiometry fixes is adaptive to each image and generally increases with image size, hence enabling optimal local adaptation even for very long image strips as typi-cally captured by a line-scanner sensor. The normalization approach is implemented in HxMap software. It has been successfully applied to large sets of heterogeneous imagery, including the adjustment of original sensor images prior to quality control and further processing as well as radiometric adjustment for ortho-image mosaic generation.

Accuracy Validation of Large-scale Block Adjustment without Control of ZY3 Images over China

Abstract. Mapping from optical satellite images without ground control is one of the goals of photogrammetry. Using 8802 three linear array stereo images (a total of 26406 images) of ZY3 over China, we propose a large-scale and non-control block adjustment method of optical satellite images based on the RPC model, in which a single image is regarded as an adjustment unit to be organized. To overcome the block distortion caused by unstable adjustment without ground control and the excessive accumulation of errors, we use virtual control points created by the initial RPC model of the images as the weighted observations and add them into the adjustment model to refine the adjustment. We use 8000 uniformly distributed high precision check points to evaluate the geometric accuracy of the DOM (Digital Ortho Model) and DSM (Digital Surface Model) production, for which the standard deviations of plane and elevation are 3.6 m and 4.2 m respectively. The geometric accuracy is consistent across the whole block and the mosaic accuracy of neighboring DOM is within a pixel, thus, the seamless mosaic could take place. This method achieves the goal of an accuracy of mapping without ground control better than 5 m for the whole China from ZY3 satellite images.

Accuracy Validation of Large-scale Block Adjustment without Control of ZY3 Images over China

Mapping from optical satellite images without ground control is one of the goals of photogrammetry. Using 8802 three linear array stereo images (a total of 26406 images) of ZY3 over China, we propose a large-scale and non-control block adjustment method of optical satellite images based on the RPC model, in which a single image is regarded as an adjustment unit to be organized. To overcome the block distortion caused by unstable adjustment without ground control and the excessive accumulation of errors, we use virtual control points created by the initial RPC model of the images as the weighted observations and add them into the adjustment model to refine the adjustment. We use 8000 uniformly distributed high precision check points to evaluate the geometric accuracy of the DOM (Digital Ortho Model) and DSM (Digital Surface Model) production, for which the standard deviations of plane and elevation are 3.6 m and 4.2 m respectively. The geometric accuracy is consistent across the whole block and the mosaic accuracy of neighboring DOM is within a pixel, thus, the seamless mosaic could take place. This method achieves the goal of an accuracy of mapping without ground control better than 5 m for the whole China from ZY3 satellite images.

Characterization of a photometric anomaly in lunar Mare Nubium

A novel approach of constructing photometrically seamless mosaics of reflectance, color-ratios, and phase–curve slopes using LROC WAC images has been developed, which can be used to map the photometric parameters of the lunar surface. The approach takes into account both geometric corrections with data on local topography and photometric conjunctions using our simple photometric model. New mosaics obtained with the technique allow more reliable studies of structural and chemical characteristics of the lunar surface. This approach has been applied to analyze the photometric anomaly (21.6S, 17.7W, ~40km in size) in Mare Nubium detected earlier with our Earth-based observations. For each point of the scene the parameters were calculated using the least-square method for several tens of source WAC images. Clementine mosaics also were used in the analysis, e.g., in order to estimate the parameter of maturity degree Is/FeO. The anomaly has low FeO and TiO2 abundance and reveals a higher slope of the phase function than surroundings. Thermal data from LRO Diviner measurements do not show anomalies in this region. We consider this area as a shallow flooding of an elevated formation of highland composition, the material of which could have been excavated and mixed up with upper layers of the lunar surface through meteoroid impacts. The anomalous behavior of the phase function can be explained by the difference of surface structure in the anomaly and surrounding regions on the scale of less than several centimeters. This may be due to larger quantities of small fragments of rocks and clumps on the surface and/or the presence of agglomerates having open structure.

Orbit optimization of Chang’E-2 by global adjustment using images of the moon

The orbit accuracy of the Chang’E-2 (CE-2) lunar probe is one of the most critical factors for a seamless mosaic of the global lunar topographic map. During the production of the CE-2 global lunar topographic map, a maximum deviation of kilometers magnitude existed in the horizontal direction of homologous points between neighboring images, while the maximum height deviation of these points is up to several hundred meters. This phenomenon indicates that current orbit determination results of CE-2 cannot truly reflect the relative position relationship between probe and lunar surface features. Against this background, global adjustment using images of the moon should be carried out to solve this problem. In this paper, the influence of CE-2 current orbit accuracy on the production of a global lunar topographic map will be analyzed based on the introduction of CE-2 observation data, including images and orbit data. Additionally, key technologies and technical processes of global adjustment using CE-2 images with high-resolution and large amounts of data will be researched. Finally, orbit optimization of CE-2 after global adjustment is analyzed, as well as the accuracy of the CE-2 global lunar topographic map for validation verification.