Historical photographs become widely used in geographical and environmental applications. Their enhancement involves converting them into georeferenced data, such as orthoimages or digital models. However no ground control points are available unlike in current image processing, and many problems such as image noise, landscape modifications, perspective distortion and unknown sensor calibration prevent automatic tie-point retrieval with current orthoimages. That is why photograph georeferencing remains a manual and time-consuming task. A novel method is presented in this paper to register photographs with current topographic database using line feature matching. Indeed, geometrical considerations only let avoid high radiometric difference issues when dealing with current orthoimages. Besides topographic database use lets selecting stable through time features, such as road network and historical buildings. A multi-scale approach allows very coarse georeferencing initialization, which can be set manually by a minimum number of ground control points per image set. At each scale an iterative processing improves the line matching and the registration model estimation at the same time. Finally, building integration makes registration more reliable for off-ground objects. Results are promising as georeferencing is much improved and its estimation converges in all test cases.
23 July 2012 in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
This article describes a pipeline developed to automatically detect and correct motion blur due to the airplane motion in aerial images provided by a digital camera system with channel-dependent exposure times. Blurred images show anisotropy in their Fourier Transform coefficients that can be detected and estimated to recover the characteristics of the motion blur. To disambiguate the anisotropy produced by a motion blur from the possible spectral anisotropy produced by some periodic patterns present in a sharp image, we consider the phase difference of the Fourier Transform of two channel shot with different exposure times (i.e. with different blur extensions). This is possible because of the deep correlation between the three visible channels ensures phase coherence of the Fourier Transform coefficients in sharp images. In this context, considering the phase difference constitutes both a good detector and estimator of the motion blur parameters. In order to improve on this estimation, the phase difference is performed on local windows in the image where the channels are more correlated. The main lobe of the phase difference, where the phase difference between two channels is close to zero actually imitates an ellipse which axis ratio discriminates blur and which orientation and minor axis give respectively the orientation and the blur kernel extension of the long exposure-time channels. However, this approach is not robust to the presence in the phase difference of minor lobes due to phase sign inversions in the Fourier transform of the motion blur. They are removed by considering the polar representation of the phase difference. Based on the blur detection step, blur correction is eventually performed using two different approaches depending on the blur extension size: using either a simple frequency-based fusion for small blur or a semi blind iterative method for larger blur. The higher computing costs of the latter method make it only suitable for large motion blur, when the former method is not applicable.
1 June 2016 in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
This paper proposes an hybrid online calibration method for a laser scanner mounted on a mobile platform also equipped with an imaging system. The method relies on finding the calibration parameters that best align the acquired points cloud to the images. The quality of this intermodal alignment is measured by Mutual information between image luminance and points reflectance. The main advantage and motivation is ensuring pixel accurate alignment of images and point clouds acquired simultaneously, but it is also much more flexible than traditional laser calibration methods.
14 June 2016 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Techniques for 3D mapping are maturing. At the same time the need for 3D data is increasing. This has pushed national (and regional) mapping agencies (NMAs) to consider extending their traditional task of providing topographic data into the third dimension. To show how research results in 3D mapping obtained over the past twenty years have been adopted by practice, this paper presents the ongoing work on 3D mapping within seven NMAs, all member of the 3D Special Interest Group of European Spatial Data Research (EuroSDR). The paper shows that some NMAs are still in the initial (experimental) phase of 3D mapping, while others have already built solid databases to maintain 2.5D and 3D topographic data covering their whole country.
26 April 2013 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Keywords: Sharpness, Haar transform, multiscale, calibration This paper proposes a method to estimate the local sharpness of an optical system through the wavelet-based analysis of a large set of images it acquired. Assuming a space-invariant distribution of image features, such as in the aerial photography context, the proposed approach produces a sharpness map of the imaging device over 16 × 16 pixels blocks that enables, for instance, the detection of optical defects and the qualification of the mosaicking of multiple sensor images into a larger composite image. The proposed analysis is based on accumulating of the edge maps corresponding to the first levels of the Haar Transform of each image of the dataset, following the intuition that statistically, each pixel will see the same image structures. We propose a calibration method to transform these accumulated edge maps into a sharpness map by approximating the local PSF (Point Spread Function) with a Gaussian blur.
7 October 2013 in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Keywords: Change detection, Digital Elevation Model, shape, persistence, multilevel Digital Elevation Models provide an accurate description of scenes allowing change detection by radiometric independence measurements. The height information gives access to the changes in the 3D shape of a scene occurring between two dates. In this paper, a procedure to extract meaningful changes is proposed based on analysing this shape variation. Instead of filtering a difference map, a multilevel analysis of the difference map based on the theory of persistence is developed to make such analysis independent from a choice of threshold values.