Multiscale Approach for Variational Problem Joint Diffeomorphic Image Registration and Intensity Correction: Theory and Application

Peng Chen, Ke Chen, Huan Han, Daoping Zhang
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引用次数: 0

Abstract

Multiscale Modeling &Simulation, Volume 22, Issue 3, Page 1097-1135, September 2024.
Abstract. Image registration matches the features of two images by minimizing the intensity difference, so that useful and complementary information can be extracted from the mapping. However, in real life problems, images may be affected by the imaging environment, such as varying illumination and noise during the process of imaging acquisition. This may lead to the local intensity distortion, which makes it meaningless to minimize the intensity difference in the traditional registration framework. To address this problem, we propose a variational model for joint image registration and intensity correction. Based on this model, a related greedy matching problem is solved by introducing a multiscale approach for joint image registration and intensity correction. An alternating direction method (ADM) is proposed to solve each multiscale step, and the convergence of the ADM method is proved. For the numerical implementation, a coarse-to-fine strategy is further proposed to accelerate the numerical algorithm, and the convergence of the proposed coarse-to-fine strategy is also established. Some numerical tests are performed to validate the efficiency of the proposed algorithm.
变分问题的多尺度方法--联合差分图像注册和强度校正:理论与应用
多尺度建模与仿真》,第 22 卷第 3 期,第 1097-1135 页,2024 年 9 月。 摘要图像配准通过最小化强度差来匹配两幅图像的特征,从而从映射中提取有用的互补信息。然而,在实际问题中,图像在采集过程中可能会受到成像环境的影响,如不同的光照和噪声。这可能会导致局部强度失真,从而使传统配准框架中的强度差最小化变得毫无意义。为解决这一问题,我们提出了一种用于联合图像配准和强度校正的变分模型。在此模型的基础上,通过引入多尺度联合图像配准和强度校正方法,解决了相关的贪婪匹配问题。我们提出了一种交替方向法(ADM)来求解每个多尺度步骤,并证明了 ADM 方法的收敛性。在数值实现方面,进一步提出了一种从粗到细的策略来加速数值算法,并确定了所提出的从粗到细策略的收敛性。为了验证所提算法的效率,还进行了一些数值测试。
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