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Trajectory abstraction is used to summarize the large amount of information delivered by the trajectory data, and trajectory restoration is used to reconstruct lost parts of trajectories. To cope with complex trajectory data, in this paper, we propose a new strategy for abstracting and restoring trajectories from the perspective of signal processing. That is, trajectories are treated as signals that...
Monte Carlo global illumination (MCGI) plays an important role for the rendering and synthesis of photorealistic image. However, the synthetic images using MCGI are always corrupted by heavy noise. Especially, very unpleasant impulse noise appears in MCGI images when 3D environments contain highly glossy surfaces. In this paper, we propose a two-stage filtering technique, by utilizing pixel samples,...
The Total Least Squares (TLS) is a denoising approach to take into the small system perturbations, and to restore the noisy images through a linear combination of the image patches. It can handle not only additive noise but also mixture noise. However, it suffers from high computational complexity and low efficiency. To this end, this paper proposes a grid-based denoising algorithm to speed up the...
In this paper, an innovative 3D visualization tool is proposed to facilitate the quickly browsing and understanding of the video sequence for users. Taking advantage of the major windows, our tool presents the multiscale key frames and the video content clearly and effectively. Namely, KF View provides a wonderful navigation of the video key frames with different levels of details. Frame View presents...
This paper proposes a novel three-dimensional (3D) visualization tool for the trajectory analysis, helping users understand the trajectory data from different perspectives. The details of a single and a set trajectories are well covered in multiscale views by the four main linked windows, namely Traj View, Color Bar, Multi Property and Track Map. We take advantage of and further improve the color...
Undoubtedly, visualization of the trajectory clustering outputs is very important and some researches have been done on visualization of the clustering results. Still importantly, the research on visualizing the procedure of clustering, which is also of great value, is little touched. In this paper, we propose a novel 3D visualization tool, which comprehensively illustrates the Agglomerative Information...
This paper proposes a novel method for image denoising based on the maximum entropy principle. For an image corrupted by Gaussian and impulse noise, impulse noise with high value is detected first using rank statistics, and then removed by a local Gaussian filter. To remove the noise left, an improved self-adaptive non-local filter, with the weights obtained based on the maximum entropy principle,...
This paper proposes a new approach for trajectory clustering and visualization. During clustering, speed and direction are both taken into account as the important properties of a trajectory. Additionally, the temporal change of the trajectories is explicitly considered in the procedure of clustering. Importantly, we introduce the uncertainty to represent the homogeneity of the updating trajectories...
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