MOE Key Laboratory of Optoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China.
Sensors (Basel). 2023 Apr 12;23(8):3922. doi: 10.3390/s23083922.
Currently, automatic optical zoom setups are being extensively explored for their applications in search, detection, recognition, and tracking. In visible and infrared fusion imaging systems with continuous zoom, dual-channel multi-sensor field-of-view matching control in the process of synchronous continuous zoom can be achieved by pre-calibration. However, mechanical and transmission errors of the zoom mechanism produce a small mismatch in the field of view after co-zooming, degrading the sharpness of the fusion image. Therefore, a dynamic small-mismatch detection method is necessary. This paper presents the use of edge-gradient normalized mutual information as an evaluation function of multi-sensor field-of-view matching similarity to guide the small zoom of the visible lens after continuous co-zoom and ultimately reduce the field-of-view mismatch. In addition, we demonstrate the use of the improved hill-climbing search algorithm for autozoom to obtain the maximum value of the evaluation function. Consequently, the results validate the correctness and effectiveness of the proposed method under small changes in the field of view. Therefore, this study is expected to contribute to the improvement of visible and infrared fusion imaging systems with continuous zoom, thereby enhancing the overall working of helicopter electro-optical pods, and early warning equipment.
目前，自动光学变焦设置正在被广泛探索，以应用于搜索、检测、识别和跟踪。在具有连续变焦功能的可见光和红外融合成像系统中，通过预校准可以实现同步连续变焦过程中双通道多传感器视场匹配控制。然而，变焦机构的机械和传输误差会导致共变焦后视场出现小的不匹配，从而降低融合图像的清晰度。因此，需要一种动态的小匹配检测方法。本文提出使用边缘梯度归一化互信息作为多传感器视场匹配相似度的评价函数，以指导连续共变焦后可见光镜头的小变焦，最终减少视场不匹配。此外，我们还展示了使用改进的爬山搜索算法进行自动变焦，以获得评价函数的最大值。因此，在视场小变化的情况下，验证了所提出方法的正确性和有效性。因此，这项研究有望改进具有连续变焦功能的可见光和红外融合成像系统，从而提高直升机光电吊舱和预警设备的整体工作性能。
