Image Fusion


Image Fusion for Context Enhancement and Video Surrealism

Ramesh Raskar,         Adrian Ilie,           Jingyi Yu

NPAR 2004

Mitsubishi Electric Research Labs

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We present a class of image fusion techniques to automatically combine images of a scene captured under different illumination. Beyond providing digital tools for artists for creating surrealist images and videos, the methods can also be used for practical applications. For example, the non-realistic appearance can be used to enhance the context of nighttime traffic videos so that they are easier to understand. The context is automatically captured from a fixed camera and inserted from a day-time image (of the same scene). Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing. We presents several results in generating surrealistic videos and in increasing the information density of low quality nighttime videos.

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