Formula for calculating spatial similarity degrees between point clouds on multi-scale maps taking map scale change as the only independent variable

The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its gener- alized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.

Robust template feature matching method using motion-constrained DCF designed for visual navigation in asteroid landing

A robust and eficient feature matching method is necessary for visual navigation in asteroid-landing missions.Based on the visual navigation framework and motion characteristics of asteroids,a robust and efficient template feature matching method is proposed to adapt to feature distortion and scale change cases for visual navigation of asteroids.The proposed method is primarily based on a motion-constrained discriminative correlation filter(DCF).The prior information provided by the motion constraints between sequence images is used to provide a predicted search region for template feature matching.Additionally,some specific template feature samples are generated using the motion constraints for correlation filter learning,which is beneficial for training a scale and feature distortion adaptive correlation filter for accurate feature matching.Moreover,average peak-to-correlation energy(APCE)and jointly consistent measurements(JCMs)were used to eliminate false matching.Images captured by the Touch And Go Camera System(TAGCAMS)of the Bennu asteroid were used to evaluate the performance of the proposed method.In particular,both the robustness and accuracy of region matching and template center matching are evaluated.The qualitative and quantitative results illustrate the advancement of the proposed method in adapting to feature distortions and large-scale changes during spacecraft landing.

Quantization Based Watermarking Methods Against Valumetric Distortions

Most of the quantization based watermarking algorithms are very sensitive to valumetric distortions, while these distortions are regarded as common processing in audio/video analysis. In recent years, watermarking methods which can resist this kind of distortions have attracted a lot of interests. But still many proposed methods can only deal with one certain kind of valumetric distortion such as amplitude scaling attack, and fail in other kinds of valumetric distortions like constant change attack, gamma correction or contrast stretching. In this paper, we propose a simple but effective method to tackle all the three kinds of valumetric distortions. This algorithm constructs an invariant domain first by spread transform which satisfies certain constraints. Then an amplitude scale invariant watermarking scheme is applied on the constructed domain. The validity of the approach has been confirmed by applying the watermarking scheme to Gaussian host data and real images. Experimental results confirm its intrinsic invariance against amplitude scaling, constant change attack and robustness improvement against nonlinear valumetric distortions.