Blind Detection and Compensation of Camera Lens Geometric Distortions

This paper presents a blind detection and compensation technique for camera lens geometric distortions. The lens distortion introduces higher-order correlations in the frequency domain and in turn it can be detected using higher-order spectral analysis tools without assuming any specific calibration target. The existing blind lens distortion removal method only considered a single-coefficient radial distortion model. In this paper, two coefficients are considered to model approximately the geometric distortion. All the models considered have analytical closed-form inverse formulae.Comment: 6 pages, 4 figures, 2 table

Analysis of pixel-mapping rounding on geometric distortion as a prediction for view synthesis distortion

We analyze the performance of the geometric distortion, incurred when coding depth maps in 3D Video, as an estimator of the distortion of synthesized views. Our analysis is motivated by the need of reducing the computational complexity required for the computation of synthesis distortion in 3D video encoders. We propose several geometric distortion models that capture (i) the geometric distortion caused by the depth coding error, and (ii) the pixel-mapping precision in view synthesis. Our analysis starts with the evaluation of the correlation of geometric distortion values obtained with these models and the actual distortion on synthesized views. Then, the different geometric distortion models are employed in the rate-distortion optimization cycle of depth map coding, in order to assess the results obtained by the correlation analysis. Results show that one of the geometric distortion models is performing consistently better than the other models in all tests. Therefore, it can be used as a reasonable estimator of the synthesis distortion in low complexity depth encoders

Theoretical analysis of electronic band structure of 2-to-3-nm Si nanocrystals

We introduce a general method which allows reconstruction of electronic band structure of nanocrystals from ordinary real-space electronic structure calculations. A comprehensive study of band structure of a realistic nanocrystal is given including full geometric and electronic relaxation with the surface passivating groups. In particular, we combine this method with large scale density functional theory calculations to obtain insight into the luminescence properties of silicon nanocrystals of up to 3 nm in size depending on the surface passivation and geometric distortion. We conclude that the band structure concept is applicable to silicon nanocrystals with diameter larger than $\approx$ 2 nm with certain limitations. We also show how perturbations due to polarized surface groups or geometric distortion can lead to considerable moderation of momentum space selection rules

Generation of curved high-order meshes with optimal quality and geometric accuracy

We present a novel methodology to generate curved high-order meshes featuring optimal mesh quality and geometric accuracy. The proposed technique combines a distortion measure and a geometric L2-disparity measure into a single objective function. While the element distortion term takes into account the mesh quality, the L2-disparity term takes into account the geometric error introduced by the mesh approximation to the target geometry. The proposed technique has several advantages. First, we are not restricted to interpolative meshes and therefore, the resulting mesh approximates the target domain in a non-interpolative way, further increasing the geometric accuracy. Second, we are able to generate a series of meshes that converge to the actual geometry with expected rate while obtaining high-quality elements. Third, we show that the proposed technique is robust enough to handle real-case geometries that contain gaps between adjacent entities.Peer ReviewedPostprint (published version

A Robust Image Hashing Algorithm Resistant Against Geometrical Attacks

This paper proposes a robust image hashing method which is robust against common image processing attacks and geometric distortion attacks. In order to resist against geometric attacks, the log-polar mapping (LPM) and contourlet transform are employed to obtain the low frequency sub-band image. Then the sub-band image is divided into some non-overlapping blocks, and low and middle frequency coefficients are selected from each block after discrete cosine transform. The singular value decomposition (SVD) is applied in each block to obtain the first digit of the maximum singular value. Finally, the features are scrambled and quantized as the safe hash bits. Experimental results show that the algorithm is not only resistant against common image processing attacks and geometric distortion attacks, but also discriminative to content changes

Geometric distortion analysis of a wide-field astrograph

Ground-based optical navigation seeks to determine the angular position of a star, Solar System body, or laser-emitting spacecraft relative to objects with well-known coordinates. Measurement accuracies of 25 nrad would make optical techniques competitive with current radio metric technology. This article examines a proposed design for a wide-field astrograph and concludes that the deviation of an image centroid from the ideal projection can be modeled to the desired accuracy provided that the field of view does not exceed 5 deg on a side