Deng Qianwei, Wong Chee-Onn, Sitharan Roopesh, Meng Xiangbin
School of Film and Television Media, Wuchang University of Technology, Wuhan, Hubei, China.
Faculty of Creative Multimedia, Multimedia University, Cyberjaya, Negeri Selangor, Malaysia.
PLoS One. 2024 Aug 8;19(8):e0307319. doi: 10.1371/journal.pone.0307319. eCollection 2024.
The utilization of digital statistical processes in images and videos can effectively tackle numerous challenges encountered in optical sensors. This research endeavors to overcome the limitations inherent in traditional focus models, particularly their inadequate accuracy. It aims to bolster the precision of real-time perception and dynamic control by employing enhanced data fusion methodologies. The ultimate objective is to facilitate information services that enable seamless interaction and profound integration between computational and physical processes within an open environment. To achieve this, an enhanced sum-modulus difference (SMD) evaluation function has been proposed. This innovation is founded on the concept of threshold value evaluation, aimed at rectifying the accuracy shortcomings of traditional focusing models. Through the computation of each gray value after threshold segmentation, the method identifies the most suitable threshold for image segmentation. This identified threshold is then applied to the focus search strategy employing the radial basis function (RBF) algorithm. Furthermore, an intelligent focusing system has been developed on the Zynq development platform, encompassing both hardware design and software program development. The test results affirm that the focusing model based on the improved SMD evaluation function rapidly identifies the peak point of the gray variance curve, ascertains the optimal focal plane position, and notably enhances the sensitivity of the focusing model.
数字统计过程在图像和视频中的应用能够有效应对光学传感器中遇到的众多挑战。本研究致力于克服传统聚焦模型固有的局限性，尤其是其精度不足的问题。它旨在通过采用增强的数据融合方法来提高实时感知和动态控制的精度。最终目标是促进信息服务，实现开放环境下计算过程与物理过程之间的无缝交互和深度融合。为实现这一目标，提出了一种增强的和模差（SMD）评估函数。这一创新基于阈值评估的概念，旨在纠正传统聚焦模型的精度缺陷。通过对阈值分割后的每个灰度值进行计算，该方法确定图像分割的最合适阈值。然后将该确定的阈值应用于采用径向基函数（RBF）算法的聚焦搜索策略。此外，在Zynq开发平台上开发了一个智能聚焦系统，涵盖硬件设计和软件程序开发。测试结果证实，基于改进的SMD评估函数的聚焦模型能够快速识别灰度方差曲线的峰值点，确定最佳焦平面位置，并显著提高聚焦模型的灵敏度。
