Asari K V, Kumar S, Radhakrishnan D
Center for High Performance Embedded Systems, Nanyang Technological University, Singapore.
IEEE Trans Med Imaging. 1999 Apr;18(4):345-54. doi: 10.1109/42.768843.
Images captured with a typical endoscope show spatial distortion, which necessitates distortion correction for subsequent analysis. In this paper, a new methodology based on least squares estimation is proposed to correct the nonlinear distortion in the endoscopic images. A mathematical model based on polynomial mapping is used to map the images from distorted image space onto the corrected image space. The model parameters include the polynomial coefficients, distortion center, and corrected center. The proposed method utilizes a line search approach of global convergence for the iterative procedure to obtain the optimum expansion coefficients. A new technique to find the distortion center of the image based on curvature criterion is presented. A dual-step approach comprising token matching and integrated neighborhood search is also proposed for accurate extraction of the centers of the dots contained in a rectangular grid, used for the model parameter estimation. The model parameters were verified with different grid patterns. The distortion-correction model is applied to several gastrointestinal images and the results are presented. The proposed technique provides high-speed response and forms a key step toward online camera calibration, which is required for accurate quantitative analysis of the images.
用典型内窥镜拍摄的图像会出现空间失真，这就需要对失真进行校正以便后续分析。本文提出了一种基于最小二乘估计的新方法来校正内窥镜图像中的非线性失真。基于多项式映射的数学模型用于将图像从失真图像空间映射到校正后的图像空间。模型参数包括多项式系数、失真中心和校正中心。所提出的方法在迭代过程中采用全局收敛的线搜索方法来获得最优扩展系数。提出了一种基于曲率准则来找到图像失真中心的新技术。还提出了一种包括令牌匹配和集成邻域搜索的双步方法，用于精确提取矩形网格中包含的点的中心，以用于模型参数估计。使用不同的网格模式对模型参数进行了验证。将失真校正模型应用于几幅胃肠道图像并展示了结果。所提出的技术提供了高速响应，是迈向在线相机校准的关键一步，而在线相机校准是图像准确定量分析所必需的。
