Camera arrangement for depth and image correspondence is very important to the computer vision. Two conventional comera arrangements for stereo computer vision are lateral model and axial motion model. In this paper, using the axial motion stereo camera model, the algorithm for camera focal length measurement and the surface smoothness with the radiance-irradiance is proposed fro 3-dimensional image correspondence on stereo computer vision. By adapting the above algorithm, camera focal length can be measured precisely and the resolution of 3-dimensional image correspondence has been improved comparing to that of the axial motion model without the radiance-irradiance relation.

Radar image data were collected through the on-line data acquisition system of A/D converter and personal computer, and the image was restorated on CRT or plotter after digital image processing of the data. The digital image processing system which was developed for this study, consisted of some kinds of software as follows : rearrangement, transformation, and enhancement of the image data in real space or frequency space by Fourier transform, edge detection of the image, compact processing, state inferential processing, and so on. Since the image of PPI radar sweeps from the center to the circumference of a circle, the image within a given period has the shape of fan. Therefore the acquired data were transformed to have the same interval as that of data in outmost concentricity. The results of various image processing methods using transformed data were better than those of the methods using original data.