2D FFT With Simultaneous Edge Artifact Removal (No. 0084)

Summary

The growth of the diagnostic imaging market is primarily driven by the increasing demand for early disease diagnosis and widening scope of clinical applications. 2D Fast Fourier Transforms (FFTs) have become a computational constraint because FFTs inherently assume that image edges are periodic leading to high amplitude “cross-shaped” artifacts in the frequency domain. These artifacts can be propagated to later stages of processing, adversely affecting decision critical applications, such as, medical diagnostics. Here, we present a promising imaging algorithm developed by a group of researchers led by Prof. Ulf Skoglund. The developed algorithm simultaneously removes edge artifacts by decomposing the image into periodic and smooth components in real-time unlike existing technologies such as windowing and mirroring which require more computational burden.

Applications

• High speed industrial tracking
• Medical diagnostics (MRI, CT, etc.)
• Electron microscopy
• Astronomical imaging
• Image processing (convolution)

Advantages

• Real-time processing
• Minimization of artifacts
• 100 fps for 2048 x 2048 pixel image