Classification of Images Using a Dictionary of Compressed Time-Frequency Atoms
Abstract
A method for automatically classifying test images based on 7 their similarities with a dictionary of example target and non- 3 target images. The method operates by receiving a test image and then initializing variables for an iteration count and for the linear expansion of the test image. The test image is then projected onto each one of the target and non-target images in the dictionary, wherein a maximum scaling coefficient is selected for each iteration. A residue is then generated, and the linear expansion of the test image is increased until a predetermined number of iterations have been performed. Once this predetermined number of iterations have been performed, the sum of the scaling coefficients belonging to the target examples in the dictionary is compared to the sum of the scaling coefficients belonging to the non-target examples in the dictionary to determine whether the image is a target signal or a non-target signal.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 30, 1998
- Accession Number
- ADD019615
Entities
People
- John M. Impagliazzo
Organizations
- United States Department of the Navy