Computational Photography with Halide

Computational Photography
Halide
C++
Implementation of image processing pipelines and computational photography algorithms using the Halide domain-specific language.
Published

May 15, 2024

A project exploring computational photography and high-performance image processing using Halide, a domain-specific language designed to make it easier to write high-performance image processing code. The project includes solutions for the MIT course 6.815/6.865 (Digital & Computational Photography) and a standalone repository containing various image processing algorithms.

Repositories: - digital-nomad-cheng/MIT-6.815 - digital-nomad-cheng/Halide_Image_Process

Key Learning Outcomes

  1. Halide DSL: Gained hands-on experience in writing fast, portable image processing code with Halide.
  2. C++ Image Processing Library: Implemented a comprehensive library of image processing algorithms from scratch using C++.
  3. ISP Pipelines: Explored the intricacies of Image Signal Processing (ISP) pipelines and their optimization.

Implementations

The project comprises various classical algorithms and operations, implemented both in pure C++ and optimized using Halide:

  • Computational Photography: High Dynamic Range (HDR) Imaging, Panorama Stitching, Image Alignment, Image Demosaicing, and Image Morphing.
  • Image Warping: Homography estimation and geometric transformations.
  • Filtering & Convolution: Box Blur, Laplacian, Median filters, and Sobel edge detection.
  • Color Operations: Color Balance, RGB to BGR conversion, and sRGB to linear RGB transformations.
  • Integration & Optimization: Seamless integration of Halide routines with OpenCV, and exploring Halide’s schedule primitives to optimize execution times across different hardware targets.

Tech Stack

C++ · Halide · OpenCV