Adaptive Filters
How To Make Adaptive Filters For Local Noise In C#
Adaptive local noise reduction filters are useful for processing images that have too much noise to deal with with other simpler filters.
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Adaptive local noise reduction filters are useful for processing images that have too much noise to deal with with other simpler filters.
Alpha trimmed mean filter is a combination of mean filters and order-statistic filters. This guide shows how to use them with C#.
Midpoint filter is a order-statistic filter and we use it to process image data in spatial domain. This guide shows how to make it with C#.
Max and min filter is one of the order-statistic filter we can use to process image data in spatial domain. This tutorial shows it with C#.
Median filter is one of the order-statistic filters for processing image data in spatial domain. This guide shows how to apply it with C#.
We can use contraharmonic mean filter to process image data in spatial domain. It's most effective against salt and pepper noise.
Harmonic mean filter is of mean filters we can use to process image data in spatial domain. This guide shows how to apply it with C#.
Geometric mean filter is one of mean filters we can use processing images in spatial domain. We use C# programming language to apply it here.
Arithmetic mean filter is one of the simplest mean filters we could use to reduce noise from an image. Learn more about spatial filtering.
Salt and pepper noise or impulse noise is one of the noise models we can use to simulate image data corruption in real life.