Random Valued Impulse Noise Reduction in Satellite Color Images Using Fast Degree of Aggregation Filtering Approach
Keywords:
Anomaly Detection, Computational Time, Noise Reduction, Vector Median Filtering, Time Scaled Root Mean Square ErrorAbstract
The suppression of random valued impulse noise in satellite data is the main focus of this article. When it comes to decreasing random valued impulsive noise in images, the vector median filters are often regarded as the highest standard. The degree of aggregation filter is a contemporary variation of this family of filters; it works by assigning each pixel a weight that is proportional to the degree to which it represents the signal component in the image. This method has the potential to enhance filtering quality by giving larger weights to pixels that seem to be similar to one another. Nevertheless, there is a major drawback to this method: filtering must be done on all of the pixels in a sequential order, which results in a very high computational cost. In this paper, we suggest a faster degree of association method that vastly improves upon the filter in concern. It is expected that the simulation would demonstrate the effectiveness of the proposed strategy. Using a combined metric of time and precision, we compared the suggested technique to the state-of-the-art approaches.
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