What are the different types of digital image processing techniques?
digital image processing techniques are usually classified into three categories. These categories include generating images, improvements and restoration. Generating techniques help the project and recognize the scanned image, while the process of improving image includes improvement of contrast, brightness and shade. Renewal techniques help eliminate and correct errors that do not exactly reflect the original picture.
Many scanners that transmit images to computer programs use the technology of optical character recognition (OCR). This converts the original image to a text that recognizes the computer program. One of the main problems with any type of image processing technology is that a certain degree of modifications is needed. Simple programs allow users to manipulate an image by shaking unnecessary space, change of shade, brightness and layout. For example, the scanner can pick up the image by creating a reflection. Digitization takes this reflection and tries to arrange it in rowsy pixels. Some forms of digitization cause this arrangement to search for variations of light recorded from the original image.
Enhancement is a wide category of digital image processing techniques that manipulate the digitized image. Computer programs can allow users to duplicate and change the scanned images. For example, color photography can be converted to black and white. Similarly, the parts of the image can be cut and translated into another.
Common techniques related to image enhancements include a change in image shade. Some of the more common improvements of the shade are related to primary colors such as red, green, blue and yellow. A reached or faded picture may be clearer, which may eliminate a picture or background imperfections. The contrast can be increased or reduced according to the amount of detail to be shown.
Digital image processing techniques can thusé include restoration. Some scanned images can pick up tears or lines. The noise that may turn out to be random dots or stripes can be removed using exchange techniques. Replicas of the average recorded scan lines Replace defective or missing pixels.
Restore may also include the use of digital filtering. This is one of the techniques of digital images that are used to eliminate dots or image spots. Any pixel that falls outside the average values range is usually eliminated when filtering is used. Pixels that fall outside the average range are usually displayed as dark or lighter spots in the picture.