We present a method to automatically detect dust and scratches on photographic material, in particular silver halide film, where traditional methods for detecting and removing defects fail. The film is digitized using a novel setup involving crosspolarization and dark-field illumination in a cardinal light configuration, which compresses the signal and highlights the parts that are due to defects in the film. Applying a principal component analysis (PCA) on the four cardinal images allows us to further separate the signal part of the film from the defects. Information from all four principal components is combined to produce a surface defect mask, which can be used as input to inpainting methods to remove the defects. Our method is able to detect most of the dust and scratches while keeping false-detections low.