Automatic Content-aware Non-Photorealistic Rendering of Images
This work addresses the need for automated, content-aware image manipulation in computational photography, though it appears incremental as it builds on existing edge-preserving filter methods.
The authors tackled the problem of generating non-photorealistic rendering effects by proposing a content-aware framework that manipulates visually salient and non-salient regions separately, enabling automatic generation of effects like detail exaggeration, artificial blurring, and image abstraction with seamless blending.
Non-photorealistic rendering techniques work on image features and often manipulate a set of characteristics such as edges and texture to achieve a desired depiction of the scene. Most computational photography methods decompose an image using edge preserving filters and work on the resulting base and detail layers independently to achieve desired visual effects. We propose a new approach for content-aware non-photorealistic rendering of images where we manipulate the visually salient and the non-salient regions separately. We propose a novel content-aware framework in order to render an image for applications such as detail exaggeration, artificial blurring and image abstraction. The processed regions of the image are blended seamlessly for all these applications. We demonstrate that content awareness of the proposed method leads to automatic generation of non-photorealistic rendering of the same image for the different applications mentioned above.