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Mikkel Lydholm Rasmussen
Mikkel Lydholm Rasmussen
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Similar to what @WhiteboxDev suggested, another filter type that could be used is a sieve filter. Instead of looking at whether the 0s or 1s "win" for a given region, it looks at the number of neighbours a given pixel has, that matches its starting value, and chains those neighbours together.

For example, the following case:

0 0 0  
1 1 1  
0 0 0

With a majority filter, this would end up as all 0, while a sieve filter, with threshold of 3 would keep the area as is. The strength of a sieve filter is that you can keep long narrow features, which may be desirable, for some applications - for example a binary classification of flooded areas, where a majority filter could end up removing well defined streams.

The filter can be found in GDAL and a UI for it is implemented in QGIS.

Similar to what @WhiteboxDev suggested, another filter type that could be used is a sieve filter. Instead of looking at whether the 0s or 1s "win" for a given region, it looks at the number of neighbours a given pixel has, that matches its starting value, and chains those neighbours together.

For example, the following case:

0 0 0  
1 1 1  
0 0 0

With a majority filter, this would end up as all 0, while a sieve filter, with threshold of 3 would keep the area as is. The strength of a sieve filter is that you can keep long narrow features, which may be desirable, for some applications - for example a binary classification of flooded areas, where a majority filter could end up removing well defined streams.

Similar to what @WhiteboxDev suggested, another filter type that could be used is a sieve filter. Instead of looking at whether the 0s or 1s "win" for a given region, it looks at the number of neighbours a given pixel has, that matches its starting value, and chains those neighbours together.

For example, the following case:

0 0 0  
1 1 1  
0 0 0

With a majority filter, this would end up as all 0, while a sieve filter, with threshold of 3 would keep the area as is. The strength of a sieve filter is that you can keep long narrow features, which may be desirable, for some applications - for example a binary classification of flooded areas, where a majority filter could end up removing well defined streams.

The filter can be found in GDAL and a UI for it is implemented in QGIS.

Source Link
Mikkel Lydholm Rasmussen
Mikkel Lydholm Rasmussen
  • 6.5k
  • 15
  • 23

Similar to what @WhiteboxDev suggested, another filter type that could be used is a sieve filter. Instead of looking at whether the 0s or 1s "win" for a given region, it looks at the number of neighbours a given pixel has, that matches its starting value, and chains those neighbours together.

For example, the following case:

0 0 0  
1 1 1  
0 0 0

With a majority filter, this would end up as all 0, while a sieve filter, with threshold of 3 would keep the area as is. The strength of a sieve filter is that you can keep long narrow features, which may be desirable, for some applications - for example a binary classification of flooded areas, where a majority filter could end up removing well defined streams.