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Art of Science

is an annual Princeton exhibition that celebrates the artistic creations in scientific research. The following artwork of mine titled "Tree" is based on my research in image processing. It received the second place in the 2011 Art of Science Competition. The exhibition was on display in the Friend Center atrium gallery from October 2011 to October 2012. More recently, this artwork was featured on the cover of Princeton's anual research magazine Discovery: Research at Princeton .

Media Coverage

New York Times NYTimes.com
Town Topics A local newspaper in Princeton

The Other One in the Series

In this other artwork that's not included in the exhibition, I applied the same process on a different image. This is a black-and-white image of a branch of the Ginkgo biloba, one of the oldest living tree species on earth.

The Full Description

As part of my research I am designing intelligent image decomposition algorithms that split an image into sub-images in a way that best captures important image structure. Natural images have structure. Understanding this structure and being able to decompose an image in a way that respects this structure is an important aspect of computational image processing.

The algorithm used here recursively cuts an image into smaller rectangular pieces. For each cut, a larger rectangle is divided either horizontally or vertically into two equal smaller rectangles. This results in a division of the input image into many rectangular pieces, similar to those shown, organized into a data structure called a dyadic tree.

For each input image, our algorithm finds the dyadic tree that gives the most concise representation of the image as measured by its Haar wavelet transform coefficients computed on this tree. We have shown that this optimal tree provides the best approximation of the sublevel sets of the image and is useful in tasks such as removing unwanted noise in the image.

To visualize how the decomposition algorithm works, I developed computer code that displays the resulting dyadic tree. The input image has been automatically cut into local rectangular pieces in a way carefully designed to achieve a useful global optimality.

For clarity, only a partial decomposition of the input image has been shown. This visualization reminds us of the inspirations we receive from nature: that harmony is required between division and unity.

Read the Paper

If you're interested in the science behind the art, you can start with the following paper. You can also find more publications related to this topic on the homepage.