基于递归滤波的声纳视频图像实时降噪

Hyeonwoo Cho, Juhyun Pyo, Jeonghwe Gu, Hangil Jeo, Son-cheol Yu
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引用次数: 3

摘要

前视成像声纳是水下视觉测量的前瞻性解决方案,因为它可以在浑浊水中实现远距离可见,并提供高帧率。然而,声图像会受到散斑噪声的影响。本文提出了一种降低前视成像声纳所获得的一系列声图像帧中的噪声的算法。建立了声学图像的时间序列模型,用于预测像元坐标的变化。同时,卡尔曼滤波器根据声学图像模型估计图像的降噪像素。这种递归处理方法适用于连续图像帧。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time noise reduction for sonar video image using recursive filtering
The forward-looking imaging sonar is a prospective solution for underwater visual surveying because it allows longrange visibility in turbid water, and provides a high frame rate. However, the acoustic images are degraded by speckle noise. In this paper, we propose an algorithm to reduce the noise in a series of acoustic image frames obtained by using a forward-looking imaging sonar. The time-series model of the acoustic images are developed for predicting the changes in pixel coordinates. Also, the Kalman filter estimates the noise-reduced pixels of the images based on the acoustic image model. This recursive treatment is suitable for the successive image frames.
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