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Automatic Image Colorization

This repository contains the code for our course project for CS663 - Fundamentals of Digital Image Processing at IIT Bombay. We implemented the following paper/report: http://cs229.stanford.edu/proj2013/KabirzadehSousaBlaes-AutomaticColorizationOfGrayscaleImages.pdf. The published code was written in Python using OpenCV, scikit-learn and pygco. We were unable to execute it since some of the functions were outdated. We have coded our implementation in MATLAB.

Team

  • Utkarsh Gupta (@Ug48)
  • Yash Shah (@ys1998)

Procedure

See the report.

Results

1. Using SVMs followed by Graph Cut Optimized Labelling

For details see the report.

2. Using k-Nearest Neighbor Search

In order to incorporate kNN search into our algorithm, we had to make the following changes - (1) remove quantization of color space, (2) replace SVM classifiers with a kNN search, (3) remove position-based features from the feature vectors and (4) replace the graph-cut labeling algorithm with a weighted average in a-b space. We were able to get significantly better results. Some of them are shown below:

(1) Same image used as reference and test image

(2) Different images used as reference and test image

(3) Multiple reference images

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Automatic colorization of grayscale images using kNN search on local features

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