Water Non-Water Segmentation Systems And Methods

A method of producing a navigation (range) chart comprising: receiving an image 3440; segmenting the image into water and non-water pixels; and generating a range chart corresponding to the environment about the mobile structure 3450. Generation of the range chart may be performed by a convolutional autoencoder or a self-supervised neural network 3420. The BEV network 3420 may be trained using a semantic segmentation network that is trained on labelled bird eye view images. The BEV network: receives a horizon stabilised visible spectrum image and infrared image from mounted imagers; fuses the visible spectrum and infrared images; creates an autoencoded birds eye view (BEV) image from the fused image; and segments the BEV autoencoded image into water and non-water features using a graph cut image segmenter. The navigation chart may comprise a range of each pixel from the imager, displayed through a range contour (2922, Fig.29). The range (navigation) chart may be augmented with: information derived from other sensors such as navigational sensors (338, 350, Fig.3); and movements of detected objects (Fig.7). Detected objects may be subject to three dimensional point cloud imaging.