Integrative Multi-Spectral Sensor Device for Far-Infrared and Visible Light Fusion

Qiao, Tiezhu; Chen, Lulu; Pang, Yusong; Yan, Gaowei

doi:10.1007/s13320-018-0401-4

Cited by 3 publications

(1 citation statement)

References 22 publications

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“…Achieving effective matching depends on a sensitive field-of-view matching similarity measure, an effective autozoom search algorithm, and a fast implementation of the algorithm. For the fixed-focus systems, fast registration and fusion can be achieved by designing a dualband imaging FOV and pre-calibration [1,8]. For the visible/infrared dual-band fusion imaging systems with continuous zoom (as shown in Figure 1), although the design and pre-calibration can allow the dual-channel field-of-view matching control in the process of synchronous continuous zoom [9], mechanical and transmission errors of the zoom mechanism can still result in a small mismatch of the dual-channel FOV after co-zooming, thus degrading the sharpness of the fusion image and affecting object observation, recognition, and tracking.…”

Section: Introductionmentioning

confidence: 99%

Small Zoom Mismatch Adjustment Method for Dual-Band Fusion Imaging System Based on Edge-Gradient Normalized Mutual Information

Chen

Liu

Jin

et al. 2023

Sensors

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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.

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Section: Introductionmentioning

confidence: 99%

Small Zoom Mismatch Adjustment Method for Dual-Band Fusion Imaging System Based on Edge-Gradient Normalized Mutual Information

Chen

Liu

Jin

et al. 2023

Sensors

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show abstract

Crystal growth and fluorescence of downconversion films in confined space with ingoing channels

et al. 2022

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Wireless Sensor System of UAV Infrared Image and Visible Light Image Registration Fusion

Meng

2022

Journal of Electrical and Computer Engineering

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The application of multisource sensors to drones requires high-quality images to ensure it. In simultaneous interpreting two or more multisensor images based on the same scene or target, the image obtained by the UAV sensor is limited by the imaging time and the shooting angle. The images obtained may not be aligned in the spatial position, thus affecting the fusion effect. Therefore, different sensor images must be registered before image fusion. During the shooting process of the drone imaging sensor, imaging angle, and environmental conditions, the obtained various sensor images will have rotation, translation, and other deformations in the spatial position so that they do not reach the spatial position. Therefore, it is impossible to directly perform image fusion directly. Therefore, before the multisensor image fusion, the image registration process must be completed to ensure that the two images are aligned in space. This paper analyzes the principles; based on the principles of the Powell search algorithm and improved walking algorithm, an algorithm combining Powell and improved walking algorithm is proposed. This paper also studies several traditional image neutrosophic fusions. The algorithm combines the fusion optimization algorithm proposed in this paper greatly reduces the calculation speed and improves the performance of the optimization algorithm and success rate.

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Integrative Multi-Spectral Sensor Device for Far-Infrared and Visible Light Fusion

Cited by 3 publications

References 22 publications

Small Zoom Mismatch Adjustment Method for Dual-Band Fusion Imaging System Based on Edge-Gradient Normalized Mutual Information

Small Zoom Mismatch Adjustment Method for Dual-Band Fusion Imaging System Based on Edge-Gradient Normalized Mutual Information

Crystal growth and fluorescence of downconversion films in confined space with ingoing channels

Wireless Sensor System of UAV Infrared Image and Visible Light Image Registration Fusion

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