The performance of image sensors highly depends on illumination conditions. As an alternative, image sensors with a logarithmic response are capable of acquiring illumination-invariant images. Planty of theoretical and applied papers have been published around the logarithmic image processing (LIP) model from its creation until today, proving its efficiency in particular for images acquired under uncontrolled and/or very low lighting. Such a model deals with grey level as well as color images. Other different yet similar models have been proposed such as the SLIP (symmetric LIP), the GLIP (generalized LIP), the PLIP (parametrization of LIP), etc., offering new concepts and various applications.
The Special Issue aims at focusing on state-of-the-art research in the domain of logarithmic imaging and sensing, including new developments currently arising linked with artificial intelligence and deep learning, with mathematical morphology or with other existing theories and successfully applied in various fields (biomedical, industry, safety, military, etc.).