Abstract
Abstract. This paper entails a methodological novelty and builds upon prior research on a wavelets-based model for digital camera self-calibration. We introduce a new kernel function based on the compactly supported orthogonal third-order asymmetric Daubechies wavelet to correct systematic image distortion errors. Tests are done by using aerial images taken with a high-resolution metric digital aerial mapping camera. The quality of experimental results is evaluated by using reliable and high precision ground check points in the calibration field. For example, a four-fold block with this wavelet self-calibration model has the external accuracy of about 0.28 GSD (=ground sampling distance) in the horizontal direction, and about 0.43 GSD in the vertical direction, respectively, where 1GSD ≈ 4.6cm. The posterior standard deviations σ̂0 of unit weight are reduced from 0.37 pixel to 0.27 pixel. The residual vector lengths are also significantly reduced after our wavelet additional parameters are used. Experimental results support the proposal and demonstrate the applicability of this new model.
Highlights
Digital images are widely used to record geometric, radiometric and semantic information in a target scene of interest
The average residual vectors of all photo coordinate observations in the cases of “without wavelet additional parameters (WAPs)” and “with WAPs” are displayed in Figure 5 and Figure 6, respectively. They illustrate that the average residual vectors of the photo coordinate observations have no significant systematic errors, and these residual vector lengths are significantly reduced after WAPs are used. These test results indicate that this wavelet model for self-calibrated bundle block adjustment is helpful and applicable to correct the systematic distortion errors of images taken with aerial digital mapping cameras
We develop novel wavelet additional parameters (WAPs) for self-calibrating digital frame cameras in the Cartesian coordinate system of Euclidean space
Summary
Digital images are widely used to record geometric, radiometric and semantic information in a target scene of interest. In order to implement the novel ideas and to explore the possible application potential of wavelets on self-calibrating distortion parameters of modern diverse types of digital cameras, the orthogonal wavelet functions are adopted and used as the mathematical basis functions to establish new camera self-calibration APs, called wavelet APs (WAPs), in our studies since 2016. The WAPs have similar advantages as Fourier APs such as mathematical rigorousness, orthogonality between any two wavelet (child) functions, model flexibility, generic applicability and computation efficiency for camera self-calibration. Some wavelets such as both asymmetric and least asymmetric families of Daubechies wavelets still have advantages in expressing both stationary and.
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