Filtering in Computer Graphics
It means that eliminating the high frequencies, combining the super-samples to compute a pixel colour. This type of filtering is known as Unweighted filtering because each supersamples to compute a pixel, irrespective of its position, it has equal influence in determining the pixel’s colour. In other words, unweighted filtering computes an unweighted average.
In weighted filter, each super-sample is multiplied by its corresponding weight and the products are summed to produce a weighted average which is used as the pixel colour. The weighting is given to each sample should depend in some way on its distance from the centre of the pixel. The centre sample within a pixel has maximum weight. an array of values specifying the relative importance weights of sub-pixels can be set for different sized grids and it is often referred to as Pixel-Weighting Masks.
Types of Filtering:
There are mainly 3 Types of Filtering.
1. Increase the resolution display (High Resolution)
Increase the resolution display:
As the aliasing problem is due to low resolution, one easy solution is to increase the resolution, causing sample points to occur more frequently. Using high resolution, the jaggies become so small that jagged edges get blurred out and edges appear smooth.
Post-filtering or Supersampling:
In Post-filtering method, more than one sample is sampled per pixel. How? Every pixel area on the display surface is assumed to be subdivided into a grid of smaller sub-pixels is known as Super-Samples.
Pre-filtering or Area-Sampling:
Pre-filtering methods treat a pixel as an area and computes pixel colour based on the overlap of the scene’s objects with a pixel’s area. These techniques compute the shades of grey-based on how much of a pixel’s area is covered by an object.