Objective High-precision component manufacturing imposes increasingly stringent requirements on surface defect inspection and three-dimensional (3D) topography measurement, particularly in advanced manufacturing fields such as semiconductor fabrication and precision micro–nano engineering. Laser confocal microscopy, owing to its excellent lateral resolution, strong optical sectioning capability, and robustness to environmental disturbances, has become an important tool for high-accuracy surface metrology. Nevertheless, conventional confocal microscopy systems are fundamentally constrained by their serial point-scanning imaging mode, which leads to limited imaging efficiency and restricts their applicability in high-throughput and real-time industrial inspection scenarios. To overcome these limitations, this study aims to develop a high-performance optical surface metrology system based on parallel-detection confocal microscopy, achieving a balanced optimization of imaging speed, resolution, and signal-to-noise ratio (SNR).

Methods To address the throughput limitations of conventional point-scanning confocal systems, this study introduces a multi-detector parallel imaging architecture that enables simultaneous acquisition of multiple confocal signals, significantly improving data acquisition efficiency. The system employs a 405 nm laser as the illumination source and integrates a resonant-galvanometer scanning module to enable high-speed two-dimensional raster scanning. In the detection path, a fiber array comprising one central fiber and six peripherally arranged fibers couples the return beam into seven independent photomultiplier tubes (PMTs), facilitating parallel signal acquisition.

Based on this parallel detection framework, two complementary operational strategies are developed. First, a pixel-displacement rearrangement algorithm is implemented to fuse images acquired from multiple detectors. By integrating information from the central and peripheral detection channels, this approach effectively alleviates the inherent trade-off between SNR and spatial resolution encountered in traditional single-detector confocal systems, enabling high imaging quality to be maintained without sacrificing throughput. Second, by fully exploiting the spatial arrangement characteristics of the detector array, a dedicated fast scanning mode is developed. This scanning strategy allows multiple spatially offset detection channels to contribute to a single image frame, thereby enhancing temporal sampling efficiency.

To ensure stable and reliable system performance, several critical calibration and correction techniques are implemented. A multi-PMT gain calibration method is developed using a uniform illumination source to compensate for response variations among parallel detection channels, ensuring signal consistency and accuracy during multi-channel image fusion. For scanning distortion correction, a hardware-independent algorithm based on piecewise cubic Hermite interpolating polynomial (PCHIP) is proposed to address the nonlinear scanning distortion introduced by the resonant galvanometer. This method interpolates discrete distortion data obtained from standard grid imaging, maintaining high smoothness while exhibiting strong adaptability to complex and spatially varying distortion patterns. Additionally, to mitigate axial systematic errors and improve the reliability of 3D reconstruction, a software-based engineering axial calibration and compensation method is established. This approach uses a high-flatness reference mirror to acquire the system's inherent axial error distribution, which is then applied as a real-time correction factor for subsequent measurements.

Results and Discussions Experimental evaluations validate the effectiveness of the proposed system and methods. In terms of imaging speed, the dedicated fast scanning mode achieves up to a 3.5-fold improvement in imaging frame rate compared with conventional confocal scanning approaches, while preserving spatial resolution and contrast. The pixel-displacement rearrangement algorithm enables the parallel detection framework to achieve a superior balance between SNR and resolution, outperforming conventional single-channel confocal imaging under identical gain settings.

For scanning distortion correction, quantitative evaluations demonstrate that the proposed PCHIP-based algorithm achieves a correction standard deviation of 4.151%, representing a 59.403% improvement in geometric correction accuracy compared with commonly used global quadratic fitting and local segmental fitting approaches. This significant enhancement confirms the method's superior adaptability to complex distortion profiles and its effectiveness in high-speed scanning scenarios.

In terms of axial measurement precision, the system retains the excellent optical sectioning capability of confocal microscopy. Experimental results demonstrate that the developed system achieves an axial measurement standard deviation of 4 nm when measuring a 1.8 μm standard height step using a 100×, 0.95 NA objective. The software-based axial calibration and compensation method effectively mitigates systematic errors, enhancing the consistency and robustness of 3D reconstruction results without increasing system complexity or requiring additional hardware.

The practical applicability of the system is further validated through two-dimensional and three-dimensional measurements of representative industrial samples, including semiconductor lithography structures and silicon-based wafer specimens. These experiments confirm that the system delivers excellent performance in both critical dimension detection and surface topography characterization, demonstrating its suitability for in-line inspection and quality control in advanced manufacturing environments.

Conclusions This study successfully develops a high-performance optical surface metrology system based on parallel-detection confocal microscopy. By introducing a multi-detector parallel imaging architecture combined with a pixel-displacement rearrangement algorithm, the system effectively overcomes the inherent trade-off between SNR and spatial resolution that limits conventional confocal systems. The dedicated fast scanning mode, enabled by the spatial arrangement of the detector array, achieves up to a 3.5-fold improvement in imaging frame rate, delivering superior performance in imaging speed, resolution, and SNR. The complementary techniques developed—multi-PMT gain calibration, PCHIP-based scanning distortion correction (achieving 59.403% accuracy improvement), and software-based axial field compensation—provide a comprehensive solution for ensuring data fidelity, geometric accuracy, and measurement precision. With an axial measurement standard deviation of 4 nm on a 1.8 μm standard sample and demonstrated efficacy on semiconductor lithography and silicon-based wafer specimens, the system meets the demanding requirements for high-resolution, high-efficiency, and high-stability surface characterization in semiconductor manufacturing and precision engineering. Overall, this work provides an efficient, high-precision, and scalable optical surface metrology solution, offering significant potential for in-line inspection and quality control in advanced industrial manufacturing environments while establishing a feasible system architecture for developing advanced optical metrology instruments.