Close-range Images Research Articles

Kaiser filter for antialiasing in digital photogrammetry

AbstractImage aliasing is a problem appearing as artefacts in digitally resampled images, which degrades the quality of the image. In digital rectification and texture mapping, pixels from an input image are transformed to pixels of an output image. The discrete nature of a digital image causes aliasing in the transformed image. In this paper the source of aliasing and the theory of antialiasing are described. The necessity of a precise filter design in antialiasing is discussed and a filter based on a Kaiser adjustable window is designed. Different practical antialiasing methods are described as well as interpolation methods, which are conventional in photogrammetry. Selected antialiasing methods are implemented and applied to a close range image. An objective analysis is carried out by applying inverse transformations to rectified images and deriving some measures to estimate the information loss for each method by comparing original and reconstructed images. Results indicate that interpolation methods are not capable of removing or reducing aliasing in highly decimating transformations. The output images of interpolation methods therefore suffer from edge corruption and interfusion of small features. Applying a Kaiser filter with a precise antialiasing method results in the least information loss and considerably reduces aliasing at the expense of higher computation load.

A Self-Adaptive Algorithm of Automatic Interior Orientation for P31 Images

Though automatic interior orientation has been deeply studied, it still remains problem for close range images photographed by P31 camera, in which fiducial marks merge in images of objects. In this paper, automatic interior orientation is regarded as a global image matching problem, which can be processed in two steps. Firstly, several possible fiducial marks are extracted with straight-line extraction by template matching and Hough transformation. Secondly, the unique fiducial marks are determined by softassign and deterministic annealing technology combined with affine transformation from the candidates fiducial marks. Experiments and discussions of parameter are also presented. It is confirmed that the fiducial marks can be determined reliably and gross error can be detected. Other strategies such as automatic determination of the minimum searching range are also taken into consideration.

Restoration and range performance in FLIR imaging systems

Image restoration of forward-looking infrared (FLIR) imagery has the potential to significantly improve the quality of image used by an automatic target recognizer (ATR) or human observer. This study investigates the feasibility of real-time image restoration algorithms and the problem of measuring image quality as it relates to target acquisition performance. This paper describes a technique for deriving small kernel filters that efficiently restore and reconstruct. Subject to implementation constraints associated with efficient application, the filters optimize image fidelity to an ‘ideal’ close-range image. The paper describes simulation experiments employing an end-to-end imaging system model, experiments with actual images using a model-based characterization of an actual imaging system, and simulation experiments that illustrate the utility of the system model and filtering in FLIR imaging system design.

Digital photogrammetry based automatic measurement of sandstone roof of a mine

Automatic close range photogrammetric measurements are of immense importance for a hazardous industry like mining. Unfortunately, available stereomatching techniques fail for high resolution close range images due to the large variation of object depth. In this paper a diffraction grating based laser dot-matrix projector along with a CCD camera is used for automatic close range measurement of a textureless and featureless object like massive sand stone strata. Targeting of object’s surface with large number of laser dots simultaneously solved two major problems: identification of conjugate points and precise image co-ordinate measurement. Least squares based template matching is used for centroid location of images of laser dots which provided 0.03 (mean) pixels accuracy. Using analytical techniques, camera model of the projector was developed by placing it rigidly on the teleseope of a geodimeter Bundle adjustment procedure is adopted for accurate estimation of interior orientation parameters of the projector which resulted precise co-ordinates of the object space during a test scan by the developed system.

LEAST SQUARES MATCHING METHOD: SOME EXPERIMENTAL RESULTS

AbstractThe effect on accuracy resulting from some changes to the conventional least squares matching method is investigated. Parallaxes computed automatically with matching methods have been compared with manual measurements made in a stereocomparator. Examples have been taken from both large and small scale aerial photographs and from close range images. Different linear geometric and radiometric parameters have been used as additional unknowns. The use of data snooping in digital matching with the least squares matching method has also been investigated. The results show that the introduction of additional affine parameters has a positive effect on the accuracy when the window size is larger than 30 × 30 pixels. The use of the data snooping technique is promising. The best precision obtained was between 10 pm and 15 μm, expressed as radial root mean square deviation, corresponding to approximately half a pixel. Gross error detection is possible to a large extent with photographs of good image quality.