Research On Key Technology Of Precision Close-Range Photogrammetry For Deformation Monitoring In Mining Area

Geological disasters in mining area get special attention over the earth, anddeformation monitoring is importance indemnificatory ways and means. Based on theclose-range photogrammetry developing trends, integrating the researching results ofcomputer vision, digital image processing, and statistical theory; as well as aiming atthe request of high precision in deformation monitoring, this paper focuses on theprecision measurement by considering many methods from multi-tache to enhanceprecision. According to the proper sequence of collection, process, location,super-resolution restoration, resolution model analysis, and engineering applicationpractice, to outspread the research.High quality image is the basic requirement. Based on analyzing theCCD/CMOS imaging theory, this paper discusses using originality signal of cameraand complementary information superabundance images, and under the guidance ofthe image quality evaluation to obtain high dynamic range image; with regard toimage noise reduction, the paper realizes the purpose of edge retentive noise reductionby using butterworth filter to improve the anisotropic diffusion equation.High precision location is the key problem of precision close-rangephotogrammetry. Based on deeply analyzing the location operator, the ellipse-fittingmethod and Butterworth Tepuy fitting were improved, which are more simple androbust. The paper brings forward location strategy which integrates statisticalapproach and geometric approach, and introduces into two kinds of geometricapproach. Based on the characteristic of Correlation Locating Algorithm, it can getrelatively high precision displacement and it brings forward a new high precisionlocation strategy by matching, super-resolution restoration, and location.As a low error bound of parameter estimating, CRLB is frequently used toevaluate arithmetic estimating performance. Combining with Monte Carlo algorithm,this paper discusses the theoretic approach to estimate the academic precision andconfidence interval of target location in certain confidence, and the academicprecision and confidence interval of fact location operator. It provides the benchmarkfor performance compare of fact location operator and the guide line for high poweredalgorithm design.Sometimes close-range photogrammetry not only requires getting the position ofmonitoring points, but also the texture compare analysis is important too. Aiming athigh precision location and full image application, it brings forward integrating Log-polar and DT-CWT super-resolution restoration method for part restoration, andself-adaptive method based on LSTMThe insufficiency of traditional close-range photogrammetry not only comesfrom the problem of digital image processing and pattern recognition algorithm, butalso is influenced by resolution model. Self-calibration method and multiple viewgeometry are introduced into the dissertation. This paper brings forward EDLTmethod for plane monitoring which considers the system error, and bundle adjustmentmodel which can be calibrated online and synchronized monitoring using imagesequences.Finally, the paper applies the method which has been discussed to similarmaterial model test and coast, and gains the better results. It proves the feasibility ofthe scheme and the accuracy of the algorithm.