Image Processing Aerial Thermal Images to determine Water ...
Transcript of Image Processing Aerial Thermal Images to determine Water ...
Algorithm Steps (approximate order)
Image Processing Aerial Thermal Images to determine Water Stress on Crops Preeyanka Shah
Department of Electrical Engineering, Stanford University
Motivation • Comprehensive crop water stress information will
enable farmers to make better decisions. Crop water stress is correlated to temperature.
• How do we better process thermal iamges from low-flying (2000 ft) crop duster into meaningful information about water stress for farmers?
Experimental Results: Orthorectification • Direct Orthorectification models are very susceptible to minor calibration issues in
both roll, pitch and yaw data to the point that raw images are better. • Methods using ground control points are time consuming and difficult to implement
with small size images
Input Image
Step 1: Orthorectify
Step 2: Correct Lens Distortion
Step 3: Correct Coloring
Step 4: Find homgraphy between images
Step 5: Stitch Images together
Step 6: Convert to thermal heat map
Future Steps: • Implement combined GCP/direct orthorectification model. • Integrate orthorectification, mosaicking and thermal heat map creation more
cohesively
Acknowledgements: Ashwin Madgavkar of Ceres Imaging Matt Yu
• SIFT based homography to orthophoto is also unsuccessful.
Experimental Results: Mosaic • Images corrected using flat field imaging and color adjustment when needed. • VL_SIFT and RANSAC based mosaicking • Two levels of mosaicking to minimize errors • From single source propagating • Pixels weighted based on distance from center
Experimental Results: Heat Map • Nonlinear equation to convert 14-bit PNG data into temperature.