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Introduction

Welcome to the fpm-py user guide! This library is designed to perform high-resolution image reconstruction using the Fourier Ptychography algorithm. Fourier Ptychography combines multiple low-resolution images taken at different illumination angles into a single high-resolution image. This process unlocks the potential of affordable imaging systems, transforming them into powerful diagnostic tools.

Key Components​

fpm-py revolves around two key components: the data structures (ImageCapture and ImageSeries) and the reconstruction algorithm (reconstruct()).

Data Structures​

ImageCapture​

ImageCapture is a data structure that represents a single image taken under a specific illumination angle. Each ImageCapture object includes:

  • The image data itself
  • The corresponding k-space vector, which is a function of the illumination angle

ImageSeries​

ImageSeries is a collection of ImageCapture objects, along with the necessary metadata for reconstruction. This metadata includes:

  • Optical Magnification: The magnification factor used during image capture.
  • Sensor Pixel Size: The physical size of each pixel on the imaging sensor.

Reconstruction Algorithm​

The core of the library is the reconstruct() function, which processes an ImageSeries to produce a high-resolution image. This function uses the Fourier Ptychography algorithm to synthesize a detailed, high-quality image from the input data.