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Advanced image processing is the use of one or more algorithms to manipulate an image or to extrapolate or hide information in it. It also can refer to embedded technologies that employ these algorithms to modify an image in real time, such as with a security camera. There are many algorithms that have been designed to address different problems with images, such as noise, edge detection and obstacle removal. Some of the uses for advanced image processing including security, medical imaging and astronomy, to name just a few.
A seemingly simple, but ultimately vital, concept in advanced image processing is that of image segmentation. This is when a part of an image, sometimes only a few pixels in size, is treated as a single unit or pixel. The value of the segment could be derived from averaging the pixels inside or any other formula. By segmenting an image, the individual segments can be compared for similarity and can help to find patterns, edges or other information. Medical imaging uses image segmentation in order to stitch together multi-planar images of the human body from different internal imaging machines.
Another important aspect of advanced image processing is the concept of edge detection. Edge detection is the way a processing program finds the boundaries of objects within an image. There are several ways to find an edge, such as finding contrasts and forming a spline between them, but there also are more advanced algorithms that also can find edges.
Through the use of advanced image processing, images can be clarified or obfuscated, enhanced or even converted into three dimensions. There are algorithms that allow programs to attempt to remove objects from an image, sometimes even permitting them to partially reveal objects behind it by using comparative data from another image. Some law enforcement programs are able to detect the edges of a person’s face, finding the dimensions between various features and then comparing them against a compiled database to see whether there is a match that determines identity.
One of the lesser known uses for advanced image processing is the ability to hide information within an image. This is part of the branch of advanced image processing that involves image compression. A seemingly normal-looking image can have actual data embedded into the image. This information can be extracted by someone who knows the key components of the algorithm that was used to place the data. Very advanced image processing programs might actually be able to extract the data independently just by recognizing a pattern.