Removing Image Artifacts Due to Dirty Camera Lenses and Thin Occluders |
 |
|
A common assumption in computer graphics, as well as in digital photography and imaging systems, is that the radiance emitted from a scene point is observed directly at the sensor. However, there are often physical layers or media lying between the scene and the imaging system. For example, the lenses of consumer digital cameras, or the front windows of security cameras, often accumulate various types of contaminants over time (e.g., fingerprints, dust, dirt). Also, photographs are also often taken through a layer of thin occluders (e.g., fences, meshes, window shutters, curtains, tree branches) which partially obstructs the scene. Both artifacts are annoying for photographers, and may also damage important scene information for applications in computer vision or digital forensics. Of course, a simple solution is to clean the camera lens, or choose a better spot to retake pictures. However, this is impossible for existing images, and impractical for some applications like outdoor security cameras, underwater cameras or covert surveillance behind a fence. Therefore, in this project, we develop new ways to take the pictures, and new computational algorithms to remove dirty-lens and thin-occluder artifacts. Unlike image inpainting and hole-filling methods, our algorithms rely on an understanding of the physics of image formation to directly recover the image information in a pointwise fashion, given that each point is partially visible in at least one of the captured images. We show that both effects can be described by a single image formation model, wherein an intermediate layer (of dust, dirt or thin occluders) both attenuates the incoming light and scatters stray light towards the camera. Because of camera defocus, these artifacts are low-frequency and either additive or multiplicative, which gives us the power to recover the original scene radiance pointwise. We develop a number of physics-based methods to remove these effects from digital photographs and videos. This project is done in collaboration with Peter Belhumeur, and Ravi Ramamoorthi. |
Publications"Removing Image Artifacts Due to Dirty Camera Lenses and Thin Occluders," |
Related Projects |