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CS
Carola Schönlieb
05/10/18
@ Y Combinator
My PhD focused on image restoration, specifically using differential equations to solve problems similar to those addressed by Photoshop's content-aware fill.
Video
YC
Mathematical Approaches to Image Processing with Carola Schönlieb
@ Y Combinator
05/10/18
Related Takeaways
CS
Carola Schönlieb
05/10/18
@ Y Combinator
The technique used for image restoration is similar to the content-aware fill feature in Photoshop, but it predates Photoshop's development.
CS
Carola Schönlieb
05/10/18
@ Y Combinator
During my research, I discovered that the Cahn-Hilliard equation was used for image restoration, which involves replacing damaged parts of a digital image with suggested content from surrounding areas.
CS
Carola Schönlieb
05/10/18
@ Y Combinator
In my postdoc, I shifted towards inverse imaging problems, where the observed data is not a direct image but a transform, such as in CT scans.
CS
Carola Schönlieb
05/10/18
@ Y Combinator
I started my research in mathematics in Vienna, focusing on partial differential equations, which model various natural phenomena in physics and biology.
JL
Joan Lasenby
09/17/18
@ Y Combinator
One of my early projects involved translating classical projective geometry concepts into geometric algebra, which simplified the mathematical complexity of computer vision tasks.
CS
Carola Schönlieb
05/10/18
@ Y Combinator
Successful image denoising methods focus on preserving edges, which are crucial for maintaining the integrity of the image's features.
CS
Carola Schönlieb
05/10/18
@ Y Combinator
For those interested in image processing, I recommend starting with foundational books and exploring recent research from institutions like UCLA.
JL
Joan Lasenby
09/17/18
@ Y Combinator
I collaborated with a motion capture company to develop algorithms for camera calibration, leveraging the unique properties of geometric algebra to enhance the process.
CS
Carola Schönlieb
05/10/18
@ Y Combinator
In collaborations with hospitals, we focus on developing algorithms that maximize the quality of high-resolution images from limited data, particularly in medical imaging.