Dirt on camera lenses, and occlusions from thin objects such as fences, are two important types of artifacts in digital imaging systems. These artifacts are not only an annoyance for photographers, but also a hindrance to computer vision and digital forensics. In this paper, 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. For dirty camera lenses, we propose two methods to estimate the attenuation and the scattering of the lens dirt and remove the artifacts -- either by taking several pictures of a structured calibration pattern beforehand, or by leveraging natural image statistics for post-processing existing images. For artifacts from thin occluders, we propose a simple yet effective iterative method that recovers the original scene from multiple apertures. The method requires two images if the depths of the scene and the occluder layer are known, or three images if the depths are unknown. The effectiveness of our proposed methods are demonstrated by both simulated and real experimental results.
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