Spatio-Colour Asplünd 's Metric and Logarithmic Image Processing for Colour Images (LIPC)
This work provides an incremental improvement for researchers in image processing and computer vision by enhancing pattern matching techniques for color images.
The paper tackles the problem of color pattern matching under varying lighting and noise by extending Asplünd's metric to a spatio-color version using the LIPC model, resulting in a metric that is insensitive to lighting variations and robust to noise.
Asplünd 's metric, which is useful for pattern matching, consists in a double-sided probing, i.e. the over-graph and the sub-graph of a function are probed jointly. This paper extends the Asplünd 's metric we previously defined for colour and multivariate images using a marginal approach (i.e. component by component) to the first spatio-colour Asplünd 's metric based on the vectorial colour LIP model (LIPC). LIPC is a non-linear model with operations between colour images which are consistent with the human visual system. The defined colour metric is insensitive to lighting variations and a variant which is robust to noise is used for colour pattern matching.