Aliasing & anti aliasing ºÝºÝߣ
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Aliasing occurs when a signal is sampled at a rate less than twice its highest frequency, resulting in apparent frequencies below what is present. This causes jagged or stair-stepped lines in digital images. Anti-aliasing techniques aim to reduce these visual defects. There are three main anti-aliasing algorithms: increasing resolution, area sampling by considering intensities over a region, and supersampling which creates a high-resolution virtual image, applies a low-pass filter, and resamples at a lower resolution. Supersampling independently supports arbitrary symmetric filters and allows wider filter coverage than hardware methods alone.
Aliasing & anti aliasing ºÝºÝߣ
- 2. What Does Aliasing Means? Digital sampling of any signal, whether sound, digital photographs, or other, can result in apparent signals at frequencies well below anything present in the original. Aliasing occurs when a signal is sampled at a less than twice the highest frequency present in the signal. In images, the repetition is in space rather than signals sampled in time for digital audio. If the image data is not properly processed during sampling or reconstruction, the reconstructed image will differ from the original image, and an alias is seen. An example of spatial aliasing is the moiré pattern one can observe in a poorly pixelated image. 2
- 3. Anti-aliasing: Definition Anti-aliasing is a technique used in digital imaging to reduce the visual defects that occur when high-resolution images are presented in a lower resolution output devices like the monitor or printer. Aliasing manifests itself as jagged or stair- stepped lines (Also known as jaggies) on edges and objects that should otherwise be smooth. With sound, aliases are removed by eliminating frequencies above half the sampling frequencies. 3
- 4. Anti-Aliasing Techniques Anti-Aliasing techniques were developed to combat the effects of aliasing. There are three main classes of anti-aliasing algorithms : 1. As aliasing problem is due to low resolution, one easy solution is to increase the resolution. This increases the cost of image production. 2. The image can be calculated by considering the intensities over a particular region. This is called Area Sampling. 3. The image is created at high resolution and then digitally filtered. This method is called supersampling or postfiltering and eliminates high frequencies which are the source of aliases. 4
- 5. 3. Anti-Aliasing : Post filtering Super sampling or post filtering is the process by which aliasing effects in graphics are reduced by increasing the frequency of the sampling grid and then averaging the results down. This process means calculating a virtual image at a higher spatial resolution than the frame store resolution and then averaging down to the final resolution. It is called post filtering as the filtering is carried out after sampling. Super sampling is basically a three stage process : * A continuous image I(x , y) is sampled at n times the frame resolution. This is a virtual image. ** The virtual image is then low pass filtered. *** The filtered image is then resampled at the final frame resolution. 5
- 6. Post-Filtering : Advantages * It support arbitrary symmetric filters at a fixed cost.. ** It allows a wider filter support. Most hardware anti- aliasing schemes only consider samples within a pixel. *** This method is independent of hardware-specific anti-aliasing methods. **** It is a simple, fast, and easy to implement Method. 6