with arcpy.EnvManager(processorType="GPU"): out_classified_raster = arcpy.ia.ClassifyPixelsUsingDeepLearning("composite_raster_for_inferencing", r"C:\path\to\model.dlpk", "padding 64;batch_size 8;predict_background True; tile_size 224", "PROCESS_AS_MOSAICKED_IMAGE", None); out_cl...
PCOT is a Python program and library which allows users to manipulate multispectral images and associated data. It is in active development in support of the ExoMars mission and intended to be used on data from the Rosalind Franklin rover, but it has much greater potential for use beyond this...
Dependencies can be installed using the Python Package Installer (pip): pip install tensorflow==1.12.0 tifffile opencv-python Running inference You can use our inference script to generate a surface water map given a multi-spectral image as: ...
While conventional algorithms struggle to find the complex correlation between image pairs, a straightforward solution is presented by deep learning models using a nonlinear end-to-end mapping of the corrupted image and the ground-truth image, $$\hat{\theta }={{\rm{\Vert }}R\left(I;\theta ...
Using it, we first demonstrate multi-spectral programmable beam steering with FOV~18° and absolute efficiencies exceeding 40%. Then, we reprogram the device to achieve multi-spectral lensing with tunable focal distance and efficiencies ~27%. Our design paves the way towards a new class of SLM...
The RX anomaly score can also be computed for an image using the flattened multispectral image vector as the input representation rather than the pixel spectrum. This representation is equivalent to the input representation for PCA (Sect.4.1). In this formulation, we compute the RX anomaly score...
In addition, similar to the OLI processing (Franz et al., 2015), to minimize the noise effects, the MSI ρt images were smoothed using a 9 × 9-element (180 m × 180 m) averaging filter. Effectively, the 443 nm band is averaged by a 3 × 3-element window and the other visible ...
The multispectral data were orthorectified using the orthomosaic map. Ground control points (GCP), such as the corners of the field blocks, were employed to enhance accuracy. From the orthomosaic image of each multispectral band, we generated six vegetation indices (VIs): normalized difference ...
The system was calibrated for variations in the spatial light intensity, using a white barium sulphate optical reference tile. Phase-2 trial: spatial image handling and segmentation method All analyses in Phase-2 were written using the Python-3 programming language, utilising the ‘SciKit-Learn’ ...
The system was calibrated for variations in the spatial light intensity, using a white barium sulphate optical reference tile. Phase-2 trial: spatial image handling and segmentation method All analyses in Phase-2 were written using the Python-3 programming language, utilising the ‘SciKit-Learn’ ...