donhdefl
9th of November 2004 (Tue), 19:55
Photo enlargement of digital pictures is done through a process called interpolation: the computation of pixel color values between the pixels that already exist. A pixel is the smallest element of an image or picture on a computer screen - usually it is a single-colored dot. All software programs that perform photo enlargement use the following pixel interpolation methods to enlarge pictures:
- Nearest neighbor interpolation
- Bilinear interpolation
- Bicubic interpolation
These photo enlargement methods and some new technologies that go beyond them are described below. The following image was the image used to show these photo enlargement method differences. The marked area was enlarged 300% in subsequent examples.
http://photoenlargement.imagener.com/images/main2.jpg
Nearest Neighbor Photo Enlargement Method
The value of the new pixel is made the same as that of the closest existing pixel. When enlarging an image the pixels or dots of color are duplicated to create new pixels increasing as the image grows. This is the least accurate method of enlarging an image, and this is obvious when you look at an image that has been enlarged using this method. This method creates obvious pixilation - edges that break up curves into steps or jagged edges, also called "jaggies." Nearest neighbor photo enlargement yields the least desirable result.
http://photoenlargement.imagener.com/images/nn.jpg
Bilinear Photo Enlargement Method
Bilinear interpolation is the next step up toward a more visually satisfying photo enhancement result. Bilinear reduces pixilation by filtering the surrounding pixels to smooth out jaggies giving the image edges a smoother look. Color values from the four surrounding pixels are sampled and filtered to provide the color value for the new pixel added during enlargement. Contrast between the jagged edges produced by the nearest neighbor enlargement method is reduced because of averaging neighboring values together.
http://photoenlargement.imagener.com/images/bl.jpg
Bicubic Photo Enlargement Method
Bicubic interpolation goes a step further than the previous two methods, analyzing the 16 pixels around each individual pixel using that information for enlargement. The weighted average of the closest 16 pixels (a 4x4 matrix) is calculated based on distance. This is the method most commonly used by popular photo software packages, and by printer driver software and many digital cameras for enlarging images. It produces smoother results but enlargements above 120% to 150%, quickly degrade in quality and become blurry.
http://photoenlargement.imagener.com/images/bl.jpg
This is the limit of the ability of all commercially available photo software, even software costing several hundred dollars. There are many software packages that have lots of functionality for manipulating images, but when it comes to photo enlargement, the above three methods have not been improved upon within their released versions.
Entire article: http://photoenlargement.imagener.com
Hope this helps...
-dh
- Nearest neighbor interpolation
- Bilinear interpolation
- Bicubic interpolation
These photo enlargement methods and some new technologies that go beyond them are described below. The following image was the image used to show these photo enlargement method differences. The marked area was enlarged 300% in subsequent examples.
http://photoenlargement.imagener.com/images/main2.jpg
Nearest Neighbor Photo Enlargement Method
The value of the new pixel is made the same as that of the closest existing pixel. When enlarging an image the pixels or dots of color are duplicated to create new pixels increasing as the image grows. This is the least accurate method of enlarging an image, and this is obvious when you look at an image that has been enlarged using this method. This method creates obvious pixilation - edges that break up curves into steps or jagged edges, also called "jaggies." Nearest neighbor photo enlargement yields the least desirable result.
http://photoenlargement.imagener.com/images/nn.jpg
Bilinear Photo Enlargement Method
Bilinear interpolation is the next step up toward a more visually satisfying photo enhancement result. Bilinear reduces pixilation by filtering the surrounding pixels to smooth out jaggies giving the image edges a smoother look. Color values from the four surrounding pixels are sampled and filtered to provide the color value for the new pixel added during enlargement. Contrast between the jagged edges produced by the nearest neighbor enlargement method is reduced because of averaging neighboring values together.
http://photoenlargement.imagener.com/images/bl.jpg
Bicubic Photo Enlargement Method
Bicubic interpolation goes a step further than the previous two methods, analyzing the 16 pixels around each individual pixel using that information for enlargement. The weighted average of the closest 16 pixels (a 4x4 matrix) is calculated based on distance. This is the method most commonly used by popular photo software packages, and by printer driver software and many digital cameras for enlarging images. It produces smoother results but enlargements above 120% to 150%, quickly degrade in quality and become blurry.
http://photoenlargement.imagener.com/images/bl.jpg
This is the limit of the ability of all commercially available photo software, even software costing several hundred dollars. There are many software packages that have lots of functionality for manipulating images, but when it comes to photo enlargement, the above three methods have not been improved upon within their released versions.
Entire article: http://photoenlargement.imagener.com
Hope this helps...
-dh