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.