Full-Vector Gradient for Multi-spectral or Multivariate Images.

Chatoux, Hermine; Richard, Noel; Lecellier, Francois; Fernandez-Maloigne, Christine · IEEE Trans Image Process · 2018

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Abstract

Gradient extraction is important for a lot of metrological applications such as Control Quality by Vision. In this work, we propose a full-vector gradient for multi-spectral sensors. The full-vector gradient extends Di Zenzo expression to take into account the non-orthogonality of the acquisition channels thanks to a Gram matrix. This expression is generic and independent from channel count. Results are provided for a color and a multi-spectral snapshot sensor. Then, we show the accuracy improvement of the gradient calculation by creating a dedicated objective test and from real images.