Bad pixel identification by means of principal components analysis

Jose ´Manuel Lopez-AlonsoJavier AldaUniversity Complutense of MadridSchool of OpticsDepartment of OpticsAv. Arcos de Jalo´n s/n. 28037 MadridSpainE-mail: jmlopez@opt.ucm.esAbstract. Bad pixels are defined as those pixels showing a temporalevolution of the signal different from the rest of the pixels of a givenarray. Principal component analysis helps us to understand the definitionof a statistical distance associated with each pixels, and using this dis-tance it is possible to identify those pixels labeled as bad pixels. Thespatiality of a pixel is also calculated. An assumption about the normalityof the distribution of the distances of the pixels is revised. Although theinfluence on the robustness of the identification algorithm is negligible,the definition of a parameter related with this nonnormality helps to iden-tify those principal components and eigenimages responsible for the de-parture from a multinormal distribution. The method for identifying thebad pixels is successfully applied to a set of frames obtained from a CCDvisible and a focal plane array (FPA) IR camera.