Image processing, a subbranch of DSP ultimately uses computer algorithms to perform the processing of a digital image. Digital images are defined over two dimensions, which makes all these algorithms multidimensional. Image processing tasks implemented in MatDeck are the most used algorithms for image enhancement and manipulation.
Image processing functions in MatDeck can be divided into numerous groups. Image acquisitions functions are used to load image files or to capture images from a camera device. Functions included are required for image manipulation and colour management. In practice, an image is manipulated in a manor so that its colour information can be derived into independent matrices and all the processing is done individually.
MatDeck’s functions for image scaling and rotations, use two-dimensional interpolation methods to obtain high quality processing. MatDeck provides advanced filtering functions. The function image median() is used to remove noise from an image by arbitrary setting the size of the neighbourhood.
Additionally, the two-dimensional box filtering function, image filter(), filter and image by a given box filter. This ensures that the image quality is enhanced by sharpening, edge detection, smoothing or other similar operations. Moreover, the built-in functions for edge detection, sharpening, smoothing motion blur effect and several other effects are included.
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.