A photograph captured by a digital camera may be the final product for
many casual photographers. However, for professional photographers,
this photograph is only the beginning: experts often spend hours on
enhancing and stylizing their photographs. These enhancements range
from basic exposure and contrast adjustments to dramatic alterations.
It is these enhancements - along with composition and timing - that
distinguish the work of professionals and casual photographers.
The goal of this thesis is to narrow the gap between casual and
professional photographers. We aim to empower casual users with
methods for making their photographs look better. Professional
photographers could also benefit from our findings: our enhancement
methods produce a better starting point for professional processing.
We propose and evaluate three different methods for image enhancement
and stylization. First method is based on photographic intuition and
is fully automatic. The second method relies on expert's input for
training; after the training this method can be used to automatically
predict expert adjustments for previously unseen photographs. The
third method uses a grammar-based representation to sample the space
of image filter and relies on user input to select novel and
Prof. Fredo Durand