Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology Complex Radiometric Interactions Sensor GENESSIS Altitude and Background Maps DIRSIG Tree DIRSIG Vehicle DIRSIG Net

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology Target Embedding V4 in Total Canopy V4 target area (oversampled 10x) V4 target area (final resolution)

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology Target Region Zoom: V5 in Partial Shade V5 target area (oversampled 10x) V5 target area (final resolution)

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology Target Phenomenology: Spectral Variation Illustrate spectral variations within a targetIllustrate spectral variations within a target –V5 shaded by tree –Ground shaded by V5 Each location plotted under different levels of model complexityEach location plotted under different levels of model complexity –Trees are opaque, no BRDF –Trees are transmissive, no BRDF Assumes the hemisphere above the target is all skyAssumes the hemisphere above the target is all sky –Trees are transmissive, BRDF Actual BRDF not availableActual BRDF not available

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology Target Phenomenology: V5 shaded by tree

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology Ground Collection: AP Hill Site Five (5) day collection missionFive (5) day collection mission –Two (2) day pre-collection site survey –Four (4) man target collection crew Thirty-five (35) ground targetsThirty-five (35) ground targets –Recorded geolocation of targets –Acquired target and surround photos –Measured sample areas on each target ~10 spectral samples per sample area~10 spectral samples per sample area Over 1,500 total spectral measurementsOver 1,500 total spectral measurements

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology Ground Collection: Post-Processing Spectral ProcessingSpectral Processing –Map spectra to targets and paint schemes –Remove noisy absorption bands –Compute spectral net transmissions Collection ProductsCollection Products –Ground Truth Report –Generic spectral database –DIRSIG specific databases

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology Scene Simulation: DIRSIG Target Vehicles Twenty-one (21) total vehicles made available for simulations.Twenty-one (21) total vehicles made available for simulations. Most vehicle geometry from U.S. Army Virtual Target CenterMost vehicle geometry from U.S. Army Virtual Target Center Camouflage nets hand constructed.Camouflage nets hand constructed. Vehicle spectra from RIT ground truth effort.Vehicle spectra from RIT ground truth effort. –Ground collect photos used to verify attributes.

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology Feature Extraction: Simplified Flow Tree Extraction Algorithm Input Image Extracted Features General approachGeneral approach –Use “circle” functions at various scales to isolate features with high radial symmetry.

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology DIRSIG Tree Extraction and Insertion Algorithm Input Color/IR Air Photo Image Externally Rendered Tree Features NIR/Red Ratio of Air Photo Image

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology DIRSIG Tree Extraction and Insertion Algorithm Input M7 Multi-Spectral Image Externally Rendered Tree Features

Digital Imaging and Remote Sensing Laboratory Rochester Institute of Technology Tree Example Simulated tree lineSimulated tree line –1000 instances of a single tree –Leaf transmission and stacking effects within the canopy are modeled. –Internal tree shadowing changes with solar angle. –GENESSIS material maps can be utilized to plant the trees in the appropriate locations.