A fusion system for combining sensor data with synthetic data to form an integrated image, the system comprising: a computer unit comprising: a synthetic vision system that receives synthetic data from a database; a sensor fusion function that receives and combines sensor data from more than one sensor; an image warping function that receives the synthetic data from the synthetic vision system and the sensor data from the sensor fusion function; wherein the image warping function maps the synthetic data into sensor data coordinates; an image registration function that receives an output from the image warping function and extracts corresponding features from the sensor data and synthetic data; wherein the image registration function matches the extracted corresponding features; and an image fusion function that receives the matched features from the image registration function and generates pixel values based on a weighted average between the synthetic data and the sensor data; wherein the corresponding features are extracted for at least two landmarks; wherein an image gradient from a sensor image dataset is extracted for each of the at least two landmarks; wherein a corresponding image gradient is extracted from a synthetic image dataset for each of the at least two landmarks; wherein a center of mass is calculated for each of the image gradients extracted from the sensor and synthetic image datasets; wherein a displacement between corresponding image gradients from the sensor and synthetic image datasets centered at the calculated centers of mass is calculated, wherein the sensor fusion function is operable to stabilize images by minimizing the displacement to form the integrated image using geometric transformation that is applied rigidly between the sensor and synthetic image datasets and a curve fitting model in a region between the at least two landmarks; and wherein the center of mass is calculated by mapping the image gradients to a central point which is the center of mass of the image gradient's curves. a computer unit comprising: a synthetic vision system that receives synthetic data from a database; a sensor fusion function that receives and combines sensor data from more than one sensor; an image warping function that receives the synthetic data from the synthetic vision system and the sensor data from the sensor fusion function; wherein the image warping function maps the synthetic data into sensor data coordinates; an image registration function that receives an output from the image warping function and extracts corresponding features from the sensor data and synthetic data; wherein the image registration function matches the extracted corresponding features; and an image fusion function that receives the matched features from the image registration function and generates pixel values based on a weighted average between the synthetic data and the sensor data; a synthetic vision system that receives synthetic data from a database; a sensor fusion function that receives and combines sensor data from more than one sensor; an image warping function that receives the synthetic data from the synthetic vision system and the sensor data from the sensor fusion function; wherein the image warping function maps the synthetic data into sensor data coordinates; an image registration function that receives an output from the image warping function and extracts corresponding features from the sensor data and synthetic data; wherein the image registration function matches the extracted corresponding features; and an image fusion function that receives the matched features from the image registration function and generates pixel values based on a weighted average between the synthetic data and the sensor data; wherein the corresponding features are extracted for at least two landmarks; wherein an image gradient from a sensor image dataset is extracted for each of the at least two landmarks; wherein a corresponding image gradient is extracted from a synthetic image dataset for each of the at least two landmarks; wherein a center of mass is calculated for each of the image gradients extracted from the sensor and synthetic image datasets; wherein a displacement between corresponding image gradients from the sensor and synthetic image datasets centered at the calculated centers of mass is calculated, wherein the sensor fusion function is operable to stabilize images by minimizing the displacement to form the integrated image using geometric transformation that is applied rigidly between the sensor and synthetic image datasets and a curve fitting model in a region between the at least two landmarks; and wherein the center of mass is calculated by mapping the image gradients to a central point which is the center of mass of the image gradient's curves.