Many methods are known in literature to reconstruct the camera response function (RF), whether they use calibration chart or images of arbitrary scenes taken at different exposures. This works in case to have at one’s disposal a camera with enough exposure steps to capture the whole dynamic range of the scene, representatively. However, in case of entry-level or low quality cameras, the resolution in the shutter time range of variation could yield just a reduced set of samples. Here we propose additional constraints to a well known method to reconstruct a RF even in the case that just a reduced set of exposures is available. Extensive experiments carried out using both a low quality and a professional camera commonly used in computer vision applications show the improvement achieved by our method in the reconstructed RF in case of few samples.
A robust approach to reconstruct experimentally the camera response function / A. Bevilacqua; A. Gherardi; L. Carozza. - STAMPA. - (2008), pp. 340-345. (Intervento presentato al convegno 1st IEEE International Workshops on Image Processing Theory, Tools & Applications tenutosi a Sousse, Tunisia nel November 23-26, 2008).
A robust approach to reconstruct experimentally the camera response function
BEVILACQUA, ALESSANDRO;GHERARDI, ALESSANDRO;CAROZZA, LUDOVICO
2008
Abstract
Many methods are known in literature to reconstruct the camera response function (RF), whether they use calibration chart or images of arbitrary scenes taken at different exposures. This works in case to have at one’s disposal a camera with enough exposure steps to capture the whole dynamic range of the scene, representatively. However, in case of entry-level or low quality cameras, the resolution in the shutter time range of variation could yield just a reduced set of samples. Here we propose additional constraints to a well known method to reconstruct a RF even in the case that just a reduced set of exposures is available. Extensive experiments carried out using both a low quality and a professional camera commonly used in computer vision applications show the improvement achieved by our method in the reconstructed RF in case of few samples.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.