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Implementation of Z. Farbman, R. Fattal, D. Lischinski, and R. Szeliski, 'Edge-Preserving Decompositions for Multi-Scale Tone and Detail Manipulation' (2008)

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Weighted Least Squares Filter

This project implements Farbman, Fattal, Lischinski, and Szeliski's "Edge-Preserving Decompositions for Multi-Scale Tone and Detail Manipulation."

Tone Manipulation

Image from author's original dataset and courtesy of Norman Koren, www.normankoren.com

As illustrated above, this filter has applications in edge-preserving smoothing, HDR tone manipulation, detail enhancement, and non-photorealistic rendering.

Usage

python tone_manipulation.py --img_path=<img_path>

  • img_path - Path to an image.

An OpenCV application showing the processed image will pop up. The controls for this application are:

  • Sliders to change the weighting between detail layers and the base layer decomposition.
  • Sliders (as proposed in the paper) to correct exposure and saturation after weighting the decomposition layers.
  • 0-3 to change the mask level of the detail mask. Masked out detail layers will not appear in the final image. a and d affect the radius of the mask cursor, and clicking the image applies the detail mask at the selected location.

Dependencies

  • Python - Tested on version 3.7.0
  • NumPy - Tested on version 1.15.0
  • OpenCV - Tested on version 3.4.1
  • Scipy - Tested on version 0.19.1

About

Implementation of Z. Farbman, R. Fattal, D. Lischinski, and R. Szeliski, 'Edge-Preserving Decompositions for Multi-Scale Tone and Detail Manipulation' (2008)

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