Fundamental Principles of Image Orientation Using Orthogonal Projection Model

The central perspective model is generally used in photogrammetry because of the high reliability, but it has a weak point that the initial values of orientation parameters are necessary due to the non-linearity. On the other hand, the model based on projective geometry, which is widely used in computer vision, can be treated as linear forms, but many indefinitenesses in the model leads to the lower precision and the lower stability. The authors developed an alternative model called the orthogonal projection model, which is as reliable as the central perspective model and does not need initial values of orientation parameters. The orthogonal projection model is derived from affine projection model with a constraint of orthogonality. The model is therefore appropriate to long distance observation like affine projection model, and it is also applicable to close range photogrammetry with high accuracy. This paper describes the derivation of the orthogonal projection model and the geometric characteristics, and also verifies the effectiveness by various simulations and a field test.