Conference Paper

A General Theory Of Time-sequential Sampling

Purdue University;
DOI: 10.1109/MDSP.1991.639321 Conference: Multidimensional Signal Processing, 1991., Proceedings of the Seventh Workshop on
Source: IEEE Xplore

ABSTRACT Not Available

0 Bookmarks
 · 
129 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a novel dynamic imaging method. This method models the object by a time-varying function, thus converting the dynamic imaging problem to a parameter identification problem. Experimental results demonstrate that this method can produce time-sequential images from a time-varying object with both high temporal and spatial resolution. The proposed method has been validated in magnetic resonance imaging by computer simulation, phantom study and animal study
    Image Processing, 1995. Proceedings., International Conference on; 01/1995
  • [Show abstract] [Hide abstract]
    ABSTRACT: Determining the parameters of motion within a time-varying scene is an important problem in such fields as computer vision, motion compensated video coding, and tracking. Most motion estimation algorithms operate on image data that has been sampled in both space and time. However, very little work has been done to investigate the impact of the underlying sampling strategy on the motion estimation problem. The authors investigate motion estimation with time-sequentially sampled image data. They consider both centroid-displacement-based and Fourier-based approaches to motion estimation with this type of data. For comparision, they also examine the performance of these estimators with conventional, frame-instantaneously sampled data. The motion estimators are developed and evaluated in the context of the tracking problem. In particular, they present extensive numerical results showing the performance of the motion estimators in a simulated tracking environment within which the assumptions underlying the development of the estimators are violated. These results suggest empirical rules for choosing parameter values for the estimators.
    IEEE Transactions on Image Processing 02/1995; 4(1):48-65. · 3.20 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper proposes a procedure to design an optimal time-sequential sampling (OTSS) for sampling the time-varying tone/color reproduction functions (TRC/CRC) of a printing process. OTSS can achieve high fidelity sensing using the least amount of sensing hardware and other resources. In particular it maximizes the time between each successive sample without resulting in aliasing. Therefore the time-varying TRC/CRC can be reconstructed with minimal reconstruction error. The reconstructed TRC/CRC are needed as feedback for color/tone consistency control. In this paper, the problem of finding OTSS is posed and solved in the context of lattice based multi-dimensional signal sampling. A computational procedure for implementation is given. Simulation studies validate the advantages of OTSS over other time-sequential samplings methods
    American Control Conference, 2006; 07/2006