A method of generating an aligned unified image using image data from at least two cameras positioned on a vehicle, the method comprising: receiving raw image data from a first camera positioned on the vehicle; converting the raw image data from the first camera into a first rectified output image using a first look-up table, the first look-up table defining at least one pixel location from the raw image data that corresponds to each pixel of the first rectified output image, the first rectified image having a perspective different from that of the raw image data from the first camera; receiving raw image data from a second camera positioned on the vehicle, wherein a field of view of the second camera partially overlaps with a field of view of the first camera; converting the raw image data from the second camera into a second rectified output image using a second look-up table, the second look-up table defining at least one pixel location from the raw image data that corresponds to each pixel of the second rectified output image, the second rectified image having the perspective different from that of the raw image data from the second camera; generating a first unified output image by combining the first rectified output image and the second rectified output image, wherein image data from the first rectified output image in the first unified output image is misaligned relative to the image data from the second rectified output image in the first unified output image; detecting a plurality of feature points in the first rectified output image and a plurality of feature points in the second rectified output image; matching each feature point of the plurality of feature points in the first rectified output image to a corresponding feature point of the plurality of feature points in the second rectified output image; determining a yaw, pitch, and roll of the first camera based on misalignments of the matched feature points; updating the first look-up table based on the determined yaw, pitch, and roll of the first camera, the method characterized in that it is further comprising: identifying a defined number of matched feature points in a region of interest that are farthest away from each other, wherein determining the yaw, pitch, and roll of the first camera based on misalignments of the matched feature points includes determining the yaw, pitch, and roll of the first camera based only on the misalignments of the identified defined number of matched feature points. receiving raw image data from a first camera positioned on the vehicle; converting the raw image data from the first camera into a first rectified output image using a first look-up table, the first look-up table defining at least one pixel location from the raw image data that corresponds to each pixel of the first rectified output image, the first rectified image having a perspective different from that of the raw image data from the first camera; receiving raw image data from a second camera positioned on the vehicle, wherein a field of view of the second camera partially overlaps with a field of view of the first camera; converting the raw image data from the second camera into a second rectified output image using a second look-up table, the second look-up table defining at least one pixel location from the raw image data that corresponds to each pixel of the second rectified output image, the second rectified image having the perspective different from that of the raw image data from the second camera; generating a first unified output image by combining the first rectified output image and the second rectified output image, wherein image data from the first rectified output image in the first unified output image is misaligned relative to the image data from the second rectified output image in the first unified output image; detecting a plurality of feature points in the first rectified output image and a plurality of feature points in the second rectified output image; matching each feature point of the plurality of feature points in the first rectified output image to a corresponding feature point of the plurality of feature points in the second rectified output image; determining a yaw, pitch, and roll of the first camera based on misalignments of the matched feature points; updating the first look-up table based on the determined yaw, pitch, and roll of the first camera, the method characterized in that it is further comprising: identifying a defined number of matched feature points in a region of interest that are farthest away from each other, wherein determining the yaw, pitch, and roll of the first camera based on misalignments of the matched feature points includes determining the yaw, pitch, and roll of the first camera based only on the misalignments of the identified defined number of matched feature points. identifying a defined number of matched feature points in a region of interest that are farthest away from each other, wherein determining the yaw, pitch, and roll of the first camera based on misalignments of the matched feature points includes determining the yaw, pitch, and roll of the first camera based only on the misalignments of the identified defined number of matched feature points.