低成本便携式多光谱成像系统的研发及优化

Objective: Hyperspectral imaging systems are widely used in various fields owing to their image-spectral characteristic and unique "spectral fingerprint" information. Multispectral imaging systems are generally less costly and more suitable for the large-scale applications compared with hyperspectral imaging systems. Nonetheless, the existing multispectral imaging systems suffer from certain problems, such as high cost, complex structure, difficult operation, and slow response time. Accordingly, a low-cost portable multispectral imaging system based on pulse modulation is proposed in this study, and its imaging parameters are optimized using the objective image quality assessment methods. Method: This system strives for a high degree of integration in a hardware design. The light source and control central processing unit(CPU) are integrated on a small printed circuit board(PCB). The 18 light emitting diode(LED) pairs of nine different wavelengths are integrated on a circular PCB board to form a circle by using a disc design. The light source can be converged, and the brightness can be improved to a certain extent. The proposed multispectral imaging system is mainly composed of a light source, a control, an image acquisition section, and an image analysis part. The light source part mainly includes nine LED arrays with the center wavelengths of 365 nm, 390 nm, 460 nm, 515 nm, 585 nm, 620 nm, 650 nm, 730 nm, and 840 nm. The control part mainly includes the self-designed LED driver circuit and universal serial bus(USB) power supply, which can light up LED arrays by sending the pulse waves at certain time intervals in time and allows the LED arrays to reach the maximum luminous intensity through the certain impedance matching. The image acquisition part primarily consists of a high-definition infrared industrial camera without the near infrared(IR) cut-off filter, which has an optimal spectral sensing range encompassing the central wavelengths of the selected nine LED arrays. The computer is used to call OpenCV through the Python language to control the camera to take images at a certain frequency. The image analysis part mainly performs the objective image quality assessment algorithms. When the system is executed, the STC89C51 microcontroller emits a pulse wave with a period of T (T is adjustable) to drive nine different wavelengths of LED arrays to light up in time. Subsequently, the computer platform calls the camera modules to capture multispectral images at matching intervals. In the system optimization experiments, we use the sharpness and the blur metrics to objectively evaluate the quality of the obtained multispectral images from three perspectives of camera shooting interval, imaging distance, and light intensity, thus obtaining better system imaging parameters. Result: The quality of multispectral images acquired from various shooting parameters and shooting conditions under three different scenarios are evaluated. Results show that the image quality of the developed multispectral imaging system is relatively good under the camera shooting interval synchronized with the bead strobe cycle of the LED arrays. The imaging distance is 25 mm, and the light intensity is 45 Lux. Conclusion: The developed multispectral imaging system based on pulse modulation is low-cost, less difficult to operate, has a simple structure, has better imaging quality, has faster imaging speed, and can meet the requirements of large-scale promotion of multispectral imaging systems for various application domains. In addition, the system design methods, design ideas, and experimental protocols covered in the current work may provide references for the subsequent studies.