Name
Abstract | ||
|---|---|---|
Space-variant, or foveating, vision architectures are of importance in both machine and biological vision. In this paper, we focus on a particular space-variant map, the log-polar map, which approximates the primate visual map, and which has been applied in machine vision by a number of investigators during the past two decades. Associated with the log-polar map, we define a new linear integral transform, which we call the exponential chirp transform. This transform provides frequency domain image processing for space-variant image formats, while preserving the major aspects of the shift-invariant properties of the usual Fourier transform. We then show that a log-polar coordinate transform in frequency (similar to the Mellin-Transform) provides a fast exponential chirp transform. This provides size and rotation, in addition to shift, invariant properties in the transformed space. Finally, we demonstrate the use of the fast exponential chirp algorithm on a database of images in a template matching task, and also demonstrate its uses for spatial filtering. Given the general lack of algorithms in space-variant image processing, we expect that the fast exponential chirp transform will provide a fundamental tool for applications in this area. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1109/34.625108 | IEEE Trans. Pattern Anal. Mach. Intell. |
Keywords | Field | DocType |
space-variant fourier analysis,space-variant image processing,frequency domain image processing,biological vision,space-variant image format,machine vision,fast exponential,primate visual map,fast exponential chirp algorithm,log-polar map,exponential chirp transform,particular space-variant map,spatial filtering,visual system,fourier transform,spatial resolution,fourier transforms,nonuniform sampling,integral transforms,frequency domain,chirp,fourier analysis,filtering,computer vision,computer architecture,real time systems,image processing,frequency domain analysis,attention,template matching | Computer vision,Constant Q transform,Non-uniform discrete Fourier transform,Harmonic wavelet transform,Pattern recognition,Computer science,Short-time Fourier transform,Artificial intelligence,Discrete Fourier transform,Hartley transform,Fractional Fourier transform,S transform | Journal |
Volume | Issue | ISSN |
19 | 10 | 0162-8828 |
Citations | PageRank | References |
15 | 1.49 | 15 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giorgio Bonmassar | 1 | 159 | 33.51 |
| E L Schwartz | 2 | 563 | 78.66 |