document: Bad pixel identification by means of principal components analysis Bad pixels are defined as those pixels showing a temporal evolution of the signal different from the rest of the pixels of a given array . Principal component analysis helps us to understand the definition of a statistical distance associated with each pixels , and using this distance it is possible to identify those pixels labeled as bad pixels . The spatiality of a pixel is also calculated . An assumption about the normality of the distribution of the distances of the pixels is revised . Although the influence on the robustness of the identification algorithm is negligible , the definition of a parameter related with this nonnormality helps to identify those principal components and eigenimages responsible for the departure from a multinormal distribution . The method for identifying the bad pixels is successfully applied to a set of frames obtained from a CCD visible and a focal plane array -LRB- FPA -RRB- IR camera
doc_bio_tags: B I I O O O B I I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B I O O O O O O O O O O O O O O O O O O O B O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I I O O O B I
extractive_keyphrases: bad pixel identification principal components analysis temporal evolution statistical distance robustness identification algorithm eigenimages multinormal distribution focal plane array ir camera
abstractive_keyphrases: ccd visible camera