Terrain images taken from an unstabilized platform by a line CCD
camera are often distorted as a result of angular motion of the line of
sight (LOS). Distortions appear as stretching, shrinking and twisting
of an image. Distorted images can be corrected by image processing
techniques. Reconstruction of distorted images is based solely on
information contained in the image and does not include inertial
measurements of the LOS angular motion.
The purpose of this work was to provide a useable image of the
scanned terrain, containing minimal distortions, to enable the user
correct orientation in the image, and the detection and recognition of
viewed objects. The reconstruction algorithm is based on crosscorrelation
between sequential image lines.
Correlation coefficients calculated for each sampled image line
serve to determine the three components of the displacement vector,
namely, lateral shift, advance rate and rotation of image lines.
Reversing of the camera scanning direction is detected by locating an
image line, which constitutes the symmetry line of a mirror image in
the received image.
The performance level of the algorithm was tested on simulated
distorted images, and real images taken by a line CCD camera. The
distortion levels at which the algorithm was tested were: Lateral shift
of sequential image lines: 0 -< 3 pixels/line, with total accumulated
shift of up to 250 pixels; sampling rate density of image lines: 0.5 -<
10 lines/pixel; rotation rate of image line: 0 -< 0.05 degrees/line,
with total accumulation of up to 10 degrees.
Reconstruction errors of 5-7% of a pixel in lateral shift
correction, 15% in line sampling rate determination and 2-8 10e-2
degrees in line rotation calculation were obtained. The ability to
successfully reconstruct distorted images with various distortion
levels within the expected dynamic range of real systems was
demonstrated. The algorithm was also shown to perform successfully
under conditions of different terrain textures.