Neighborhood averaging technique using Wiener filter and median filter methods were used to reduce image noise and to preserve edges.
Since median filtering requires a large amount of sorting and long computation time [17], a weighted fast median filtering method is adopted in this paper.
From the above experiment results, it is clear that the sparse representation method outperforms the wavelet and median filtering method not only in crack detection and main profile reconstruction but also a good separation between crack and main profile.
Compared to the wavelet and median filtering method, the cracks extracted by our method can match the shape of crack very well, which cannot damage the information of the main profile signal.
an algorithm authored by Lu and Tan [6] that proposes an AA step to extend Freeman's median filtering method by lifting the constraint of keeping the original CFA-sampled values intact.
We apply the method proposed in this paper to both synthetic and real data, and compare the results with that of the median filter based method, which is widely used in engineering practice.
In this paper, we present a weighted median guided filtering method for rain removal with a single image.
Based on what was mentioned above, in an attempt to preserve more complex structures in the rain-removed images, in this paper, we present a weighted median guided filtering method for rain removal with a single image.
To verify whether the weighted median filter employed in this method can be replaced by other de-noising filters, such as Gaussian filter, median filter, bilateral filter, and guided filter, we compare their abilities in rain removal with that of the weighted median filter in this section.
There are three typical image filtering methods: blurring filter, median filter, and bilateral filter.
