Non-rigid point set registration method based on enhanced affine transformation

Abstract

The invention discloses a non-rigid point set registration method based on enhanced affine transformation, belongs to the technical field of image processing, and relates to a point set registration method. The problem of low registration accuracy and poor robustness caused by the local convergence of the registration accuracy objective function of the existing point set registration method is solved. The invention utilizes a global non-rigid transformation model that can characterize the global deformation law to complete rough registration, and then utilizes a local non-rigid transformation model to fine-tune the results of the rough registration to realize point matching. Firstly, the global non-rigid transformation model is constructed by using the enhanced affine transformation based on nonlinear polynomial, and the registration accuracy objective function based on the Gaussian field is used to overcome the local convergence problem in the gradient optimization process and achieve coarse registration; then the coarse registration As the initial value, the local non-rigid transformation model is used to fine-tune the objective function to achieve the final point set registration.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a non-rigid point set registration method based on enhanced affine transformation. Background technique [0002] Point set registration is a key fundamental research problem in many computer vision applications, such as pattern recognition, medical image analysis, image fusion, and binocular stereo vision. Point set registration aims to find correspondences between point sets and derive spatial transformations that can change the shape of one point set to conform to another. [0003] In order to obtain high-precision registration results, researchers have proposed many methods, which can be mainly divided into two categories: rigid registration and non-rigid registration. Rigid registration only includes three transformations: translation, scaling and rotation. Since its implementation is relatively simple, there are many researches and applications on it. On the basis o...

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Problems solved by technology

[0004] At present, in most non-rigid point set registration methods, point set registration is often converted into an objective function optimization problem, and the spatial transformation model used is based on the cognition that the non-rigid deformation of each point is independent of each other. , so it is often affected by local convergence, resulting in the inability to obtain the optimal registration effect

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