Dust and scratch removal in scanned images

Dust, scratches or hair on originals (prints, slides or negatives) distinctly appear as light or dark artifacts on a scan. These unsightly artifacts have become a major consumer concern. This paper describes an algorithmic solution to the dust and scratch removal task. The solution is divided into two phases: a detection phase and a reconstruction phase. Some scanners have dedicated hardware to detect dust and scratch areas in the original. Without hardware assistance, dust and scratch removal algorithms generally resort to blurring, at the loss of image detail. We present an algorithmic alternative for dust and scratch detection that effectively differentiates between defects and image details. In addition we present reconstruction algorithms, that preserve image sharpness better than available alternatives. For detection we generate a detail-less image in which the defects are "erased". We compare properties of the luminance channel of the input image relative to the detail-less image. For reconstruction of the defective areas we suggest both a fast small support algorithm and a large support algorithm, which is better able to mimic the existing image texture.