Velocity selective filters recursively implemented in the spatiotemporal domain.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 16764284.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Energy-based methods for motion estimation in image sequences process the input data either in the spatiotemporal or in the frequency domain. In both cases, the algorithms already described in the literature often require a huge number of elementary operations. In this paper, we describe a class of velocity selective filters which yield an accurate detection of the edges moving in the sequence. We first present a filtering scheme based on a convolution operation computed on a finite size neighborhood and describe its properties in the spatiotemporal and frequency domains. Then, we show that filters with similar properties can be implemented recursively, i.e., as convolutions computed on infinite-size neighborhoods. As an example, we finally show the filters' responses in the case of two superimposed translational motions.
Medical subject headings
- Artificial Intelligence
- Image Enhancement
- Image Interpretation, Computer-Assisted
- Imaging, Three-Dimensional
- Information Storage and Retrieval
- Movement
- Video Recording