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Identifying spurious reduction artefacts in galaxy spectra is a challenge forlarge surveys. We present an algorithm for identifying and repairing residualspurious features in sky-subtracted galaxy spectra with application to theVIPERS survey. The algorithm uses principal component analysis (PCA) applied tothe galaxy spectra in the observed frame to identify sky line residualsimprinted at characteristic wavelengths. We further model the galaxy spectra inthe rest-frame using PCA to estimate the most probable continuum in thecorrupted spectral regions, which are then repaired. We apply the method to90,000 spectra from the VIPERS survey and compare the results with a subsetwhere careful editing was performed by hand. We find that the automatictechnique does an extremely good job in reproducing the time-consuming manualcleaning and does it in a uniform and objective manner across a large datasample. The mask data products produced in this work are released together withthe VIPERS second public data release (PDR-2).

The VIMOS Public Extragalactic Redshift Survey (VIPERS): PCA-based automatic cleaning and reconstruction of survey spectra