Intensity‐curvature functional‐based digital high‐pass filters |
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Authors: | Carlo Ciulla Ustijana Rechkoska Shikoska Dimitar Veljanovski Filip A Risteski |
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Affiliation: | 1. University of Information Science & Technology, “St. Paul the Apostle”, Partizanska B.B, Ohrid, Republic of Macedonia;2. Department of Radiology, General Hospital 8‐mi Septemvri, Boulevard 8th September, Skopje, Republic of Macedonia |
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Abstract: | The intensity‐curvature functional (ICF) of a model polynomial function is defined on a pixel‐by‐pixel basis by the ratio between the intensity‐curvature term before interpolation and the intensity‐curvature term after interpolation. Through the comparison with the traditional high‐pass filter (HPF), this work presents evidence that the ICFs of three model polynomial functions can be tuned as HPFs. The evidence consists of the mathematical characterization of the ICF‐based HPFs, qualitative comparisons in magnetic resonance imaging (MRI) of the human brain, and the determination of the finite impulse response (FIR) of the filters. The ICF‐based HPFs can remove periodic noise in the low‐frequency band. |
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Keywords: | finite impulse response high‐pass filter intensity‐curvature functional model polynomial function magnetic resonance imaging |
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