  We present a framework for interactive design of new image stylizations using
a wide range of predefined filter blocks. Both novel and off-the-shelf image
filtering and rendering techniques are extended and combined to allow the user
to unleash their creativity to intuitively invent, modify, and tune new styles
from a given set of filters. In parallel to this manual design, we propose a
novel procedural approach that automatically assembles sequences of filters,
leading to unique and novel styles. An important aim of our framework is to
allow for interactive exploration and design, as well as to enable videos and
camera streams to be stylized on the fly. In order to achieve this real-time
performance, we use the \textit{Best Linear Adaptive Enhancement} (BLADE)
framework -- an interpretable shallow machine learning method that simulates
complex filter blocks in real time. Our representative results include over a
dozen styles designed using our interactive tool, a set of styles created
procedurally, and new filters trained with our BLADE approach.

Graphics;Computer Vision and Pattern Recognition