Median-mean value-based underwater hybrid noise rapid filtering technology
A filtering technology and mixed noise technology, which is applied in image data processing, instruments, calculations, etc., can solve the problems of noise pollution, time-consuming, unsatisfactory filtering effect, etc., and achieve the effect of improving real-time performance and suppressing mixed noise
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Embodiment 1
[0044] The purpose of the present invention is to provide a median-mean based rapid filtering technology of underwater mixed noise, which can effectively suppress underwater mixed noise and improve the real-time performance of filtering.
[0045]Median filtering and mean filtering are the two most commonly used and practical methods in digital image processing, which are used to deal with impulse noise and Gaussian noise respectively. However, underwater optical images often contain these two types of noise at the same time. When the noise pollution is serious, the interaction between the noises will lead to a single filtering method that cannot effectively eliminate the noise, resulting in filtering failure. The invention discloses a median-mean-based rapid filtering technology of underwater mixed noise, the purpose of which is to effectively combine the median filter and the mean filter while quickly suppressing these two types of noise and improve the real-time performance o...
Embodiment 2
[0052] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following description.
[0053] Step 1: Acquire underwater visible light images;
[0054] The underwater visible light image of the present invention is completed by shooting the analog camera on the AUV at a distance of 3m from the real object at the bottom of the pool.
[0055] Step 2: Set decomposition speeds up the median calculation process;
[0056] Such as figure 2 As shown, the set decomposition accelerated median calculation process is divided into the following steps:
[0057] Step1: First assign a status flag status to each pixel of the image to be processed, initialized to 1, and the status flag is used to determine whether a pixel is successfully filtered during program execution. Determine an initial filter window W, the default window size is 3*3...
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