Presentation + Paper
26 October 2022 Improving the quality and visibility of objects in images captured in difficult weather conditions
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Abstract
The article proposes an approach to improve the visual quality of generated images based on the use of primary data processing methods. To reduce the effect of noise associated with the appearance of dust or water droplets, a multi-criteria filtering method is proposed for use. The proposed method allows two-pass processing. At the first stage, the method uses a criterion that forming strong noise suppression with blurring of the boundaries. Based on the generated data, we perform filtering while preserving and strengthening the boundaries of objects. Next, we perform the formation of a combined approach to fusion of image. In the case of low illumination, the noise component is strong and its suppression is an important problem. In the case of fog, the task is complicated, since the boundaries of objects are blurred. An adaptive non-linear alpha-contrasting algorithm is used for elimination and compensation. Pairs of test images obtained by sensors with a resolution of 6000x4000 (8 bit, color image, visible range) are used as test data used to evaluate the effectiveness, pairs of images with the same illumination but different fog density are used for the test. Images of simple shapes are used as analyzed objects.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Evgenii Semenishchev, Aleksandr Zelensky, Yury Ilyukhin, Nikolay Gapon, Marina Zhdanova, and Viacheslav Voronin "Improving the quality and visibility of objects in images captured in difficult weather conditions", Proc. SPIE 12266, Environmental Effects on Light Propagation and Adaptive Systems V, 122660I (26 October 2022); https://doi.org/10.1117/12.2641157
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KEYWORDS
Visibility

Visibility through fog

Image fusion

Air contamination

Image processing

Control systems

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