水下图像增强算法研究

Wenfang Jian
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引用次数: 0

摘要

近年来,随着人类活动区域的不断扩大,人类活动造成的海洋污染日益严重,大量涌入的农业排放物和生活垃圾需要依靠水下设备进行清理。然而,要从复杂的水下环境中识别垃圾,就必须研究水下图像增强算法。因此,本文以水下塑料漂浮物为研究对象,从水下图像的光学成像模型入手,分析水下光学成像的过程和机理,及其对图像质量的影响,从而更好地理解图像质量下降的原因。基于白平衡算法、直方图均衡算法、双边滤波算法和伽玛校正方法,对水下图像识别图像进行改进。分析并应用这些方法增强水下图像的原理,进一步提高水下图像增强的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Underwater Image Enhancement Algorithm
In recent years, with the continuous expansion of human activity areas, the Marine pollution caused by human activities has become increasingly serious, and the large influx of agricultural emissions and household garbage needs to rely on underwater equipment to clean up. However, to identify garbage from the complex underwater environment, it is necessary to study the underwater image enhancement algorithm. Therefore, this paper takes underwater plastic floaters as the research object, starts with the optical imaging model of underwater images, analyzes the process and mechanism of underwater optical imaging, and its impact on image quality, so as to better understand the causes of image degradation. Based on white balance algorithm, histogram equalization algorithm, bilateral filter algorithm and gamma correction method, the underwater image recognition image is improved. The principle of these methods to enhance underwater image is analyzed and applied to further improve the effect of underwater image enhancement.
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