Image processing, a sub branch of digital signal processing, is the use of computer algorithms to perform the processing of a digital image. Digital images are defined over two dimensions, which make all these algorithms multidimensional. Image processing tasks implemented in MatDeck are the most often used algorithms for image enhancement, and image manipulation.
Image processing functions in MatDeck can be divided into several groups. Image acquisitions functions are used to load image files or to capture images from a camera device. There are functions which are used for basic image manipulations and color management. In practice, an image is manipulated in such a manner that its color information is derived into independent matrices, and all the processing is done separately. In MatDeck, there are functions for image scaling and rotations which use two dimensional interpolation methods in order to obtain high quality processing.
MatDeck also contains advanced filtering functions. The function image median() is used to remove noise from an image by arbitrary setting the size of the neighborhood. MatDeck also has a two dimensional box filtering function, image filter(), which filters an image by a given box filter. Using this way, image quality can be enhanced by sharpening, edge detection, smoothing or other similar operations. There are also built in functions for edge detection, sharpening, smoothing, motion blur effect, and several other effects.
The MatDeck functions are illustrated in following examples:
- Image Processing in MatDeck – illustrates image acquisition and basic image and color manipulations.
- Image Rotation – illustrates MatDeck function for image rotation.
- Image Scaling – illustrates MatDeck options for image resizing.
- Image Filtering – illustrates two dimensional box filter in MatDeck.
- Image Filtering with Built-in MatDeck Function – illustrates use of median filter, and other built in functions for edge detection, sharpening, smoothing and other effects.