Design of Evaluation Index for Auto-Focusing Function and Optimal Function Selection

Yongping, 翟永平 Zhai; Dongxiang, 周东翔 Zhou; Yunhui, 刘云辉 Liu; Shun, 刘顺 Liu; Keju, 彭科举 Peng

doi:10.3788/aos201131.0418002

Cited by 14 publications

(2 citation statements)

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“…Objective metrics are essential for comparing various functions in the experiment. In this study, evaluation criteria included clarity ratio (R), sensitivity (M), and accurate assessment of the maximum image clarity value [10]. Elevating the clarity ratio (R) improves the evaluation function's ability to distinguish between focused and defocused states, while higher sensitivity (M) enhances responsiveness to precise focusing.…”

Section: Results and Analysismentioning

confidence: 99%

Image clarity evaluation functions for camera autofocus under various lighting conditions

Zhang,

Ma,

Zang

et al. 2024

International Conference on Optics and Machine Vision (ICOMV 2024)

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The multispectral imaging system captures images using multiple different light sources. As the camera focuses on different light sources, the wavelength of the light changes, causing a shift in the focal length of the camera and a corresponding change in the information captured by the image. To address this issue, this paper analyzes other evaluation functions and modifies the Tenengrad function to extract image gradient information from multiple directions. The paper then proposes the SIFTQuad_Tenen image clarity evaluation function, which is combined with the SIFT feature point extraction algorithm. Experiments were conducted using three different light sources: red, green, and blue. The resulting clarity evaluation curves and related indicators were compared with those of other evaluation functions. The results show that the proposed evaluation function has good performance in all three lighting scenarios, as well as better stability and higher sensitivity than other evaluation functions.

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Section: Results and Analysismentioning

confidence: 99%

Image clarity evaluation functions for camera autofocus under various lighting conditions

Zhang,

Ma,

Zang

et al. 2024

International Conference on Optics and Machine Vision (ICOMV 2024)

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show abstract

“…The algorithm time τ, which reflects the processing speed of the algorithm, is the time required to evaluate an image frame. The sensitivity M represents the intensity of changes of the field-of-view matching evaluation function near the maximum value [41]. It reflects the sensitivity of the evaluation function in the small field-of-view changes.…”

Section: Evaluation and Search Results For Different Scenesmentioning

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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Autofocus method based on multi regions of interest window for cervical smear images

Zhang

Jia

et al. 2022

Multimed Tools Appl

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Design of Evaluation Index for Auto-Focusing Function and Optimal Function Selection

Cited by 14 publications

References 0 publications

Image clarity evaluation functions for camera autofocus under various lighting conditions

Image clarity evaluation functions for camera autofocus under various lighting conditions

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

Autofocus method based on multi regions of interest window for cervical smear images

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