We have developed a number of image color related filters while providing solutions for some computer vision problems and developed some others just for fun. Here, we present some of the interesting ones.

  • Contrast Enhancement: as the name implies increasing the contrast of an image.
  • Style Transfer: transfering the color profile of an image to another image.
  • Decolorization with Contrast Preservation: converting a colored image to grayscale without losing its contrast information


Contrast Enhancement


The images to the right are contrast enhanced versions of the left images. Contrast enancement is performed locally and it takes about 60ms/megapixel. It's highly parallelizable and could be made to run even faster.


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Style Transfer


Style transfer is the process of likening the photographic style of an image to another one. It's highly popular nowadays in Computation Photography literature. Our results below are acquired by implementing a popular novel algorithm. The first row below contains the reference images where all the other images are likened to in the corresponding rows below.


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Decolorization with Contrast Preservation


Normal gray scale conversion is performed by weighted sum of the color channels. This, however, results in a loss of contrast in the gray converted images as it is not possible to distinguish similar but permuted valued colors (i.e red (255,0,0) and blue (0,255,0) will look very much alike when converted to gray scale). Contrast preserved decolorization approaches solve this problem by applying certain constraints on the grayscale conversion process to preserve as much contrast as possible. Below, we show some results of our implementation: Left image is the original colored image, middle one is the standard gray-scale converted image and the right one is the result of decolorization with contrast preservation.

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