Coded Aperture solution using de-convolution

Computer Vision


Project Description:

Patterned mask inserted at the aperture stop of a camera preserves high frequency components and increases the sensitivity of details sharpness to defocus. This can be used to derive depth map through an estimated blurring function as well as to control the focal plane, in order to be able to focus on different objects in an image.

This project will be done in cooperation with Intel.

  1. Image and Depth from a Conventional Camera with a Coded Aperture
  2. Dappled Photography: Mask Enhanced Cameras for Heterodyned Light Field and Coded Aperture Refocusing
Project Goal:

Use simulations for feasibility study of Z data extraction and refocus control, based on coded aperture principle.
In the first step we will use simulations (Fourier based) to create the patterned mask effect on still images. Then we will use a promising de-convolution scheme to recover Z information, given full calibration data for the defocus blurring function.

Project Details:
  1. Supervisor:
    Gur Harary
    Phone: 04-8295741/4630
  2. Requirements:
    MATLAB or C/C++
    CComputer Graphics or Image Processin

  3. Project status:
    Taken by the student Saar Yoskovitz
  4. Visit:
    Project web site
Current Projects Archive
CG&M Lab    Contact Us EE Labs ECE Department Technion