tessl/pypi-itk

Insight Toolkit for N-dimensional image processing, segmentation, and registration in medical and scientific applications

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Overview

Eval results

Files

FFT Operations

Name: tessl/pypi-itk
Author: tessl

Fast Fourier Transform operations for frequency domain analysis and filtering.

Capabilities

Forward and Inverse FFT

class ForwardFFTImageFilter:
    """Generic forward FFT filter."""

class InverseFFTImageFilter:
    """Generic inverse FFT filter."""

class FFTWForwardFFTImageFilter:
    """FFTW-based forward FFT."""

class FFTWInverseFFTImageFilter:
    """FFTW-based inverse FFT."""

class VnlForwardFFTImageFilter:
    """VNL-based forward FFT."""

class VnlInverseFFTImageFilter:
    """VNL-based inverse FFT."""

FFT Utilities

class FFTShiftImageFilter:
    """
    Shift zero-frequency component to center of spectrum.
    """
    
    def SetInverse(self, inverse):
        """Set inverse shift mode."""

class FFTNormalizedCorrelationImageFilter:
    """FFT-based normalized correlation."""

class FFTConvolutionImageFilter:
    """FFT-based convolution."""

Usage Examples

import itk

image = itk.imread('input.png', itk.F)

# Forward FFT
ImageType = itk.Image[itk.F, 2]
fft_filter = itk.ForwardFFTImageFilter[ImageType].New()
fft_filter.SetInput(image)
fft_filter.Update()
fft_image = fft_filter.GetOutput()

# Shift zero frequency to center
shifted = itk.FFTShiftImageFilter.New(fft_image)
shifted.Update()

# Inverse FFT
ifft_filter = itk.InverseFFTImageFilter.New(fft_image)
ifft_filter.Update()
reconstructed = ifft_filter.GetOutput()

Install with Tessl CLI

npx tessl i tessl/pypi-itk