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Digital image processing solutions
Digital image processing solutions

Digital image processing is a rapidly developing scientific field that is increasingly used in various information technology systems: radar, communications, television, etc. Digital image processing has many advantages over analog processing. It allows you to apply a much wider range of algorithms to input data and avoid problems such as added noise and distortion during processing. Since images are defined as two-dimensional (or higher), digital image processing solutions can be modeled as multidimensional systems.

How it all started

The first digital image processing techniques were developed in the 1960s at the jet propulsion Laboratory, the Massachusetts Institute of technology, bell Laboratories, the University of Maryland, and other research centers as applications for satellite photography, conversion to phototelegraph standards, medical imaging, video telephony, character recognition, and photo enhancement. With the growing power of General-purpose computers, almost all specialized operations that require a large amount of computer resources are performed on them. With fast computers and signal processing becoming available in the 2000s, digital image processing has become the most common form of image processing and is generally used not only because it provides the most flexible methods, but also because it is cheaper. Digital image processing allows the use of significantly more complex algorithms, and therefore can give both greater performance on simple tasks, and implement methods that would not be possible with analog implementation.

Nuances of digital technologies

Filtering: Digital filters are used to blur and sharpen digital images. Filtering can be performed in the spatial domain by convolution with specially designed cores (filtering arrays) or in the frequency domain (Fourier) by filtering out certain frequency regions.

Digital camera image: Digital cameras usually include specialized digital image processing hardware – either individual chips, or by adding circuits to other chips-to convert raw data from a photo matrix into a color-corrected image in a standard image file format.

Image analysis

Image analysis - selecting important information from an image using automatic or semi-automatic devices and systems. In the WTA literature, the area also has other names: data extraction from an image, scene analysis, image description, automatic decryption, image recognition, and so on.
Image analysis differs from classical image recognition in that analysis systems are by definition not limited to dividing areas of a scene into a fixed number of classes, but are designed to describe complex scenes, whose diversity can be so great that they cannot be described using pre-defined terms. In addition, image analysis systems often use a priori information about objects and their mutual relations. Similarly, digital image processing methods are based on the representation of digital images as an implementation of a random process. Statistical description of images allows you to analyze and filter images by processing the probability of the structure of the phase space of features (FPP).

Evaluation of images

The essence of statistical evaluation of images is as follows. The transformation of the phase space of features is performed, which leads to the suppression of information in the image that has arisen under the influence of noise. The elimination of noise information is performed by combining a number of phase States of the original image, so their number in the statistical estimation is always less than in the original image, and the entropy of the statistical estimation is less than that of the original image. Digital image processing is any form of information processing for which input data is represented by an image, such as photos or video frames. Image processing can be performed both to obtain an output image (for example, preparing for printing, broadcasting, etc.), and to obtain other information (for example,recognizing text, counting the number and type of cells in the field of a microscope, etc.). In addition to static two-dimensional images, it is also necessary to process images that change over time, such as video.

A little background. Back in the mid-twentieth century, image processing was mostly analog and performed by optical devices. Such optical methods are still important in areas such as holography. However, with the rapid increase in computer performance, these methods were increasingly replaced by digital image processing methods. Digital image processing methods are usually more accurate, reliable, flexible, and easy to implement than analog methods. In digital image processing, specialized equipment is widely used, such as processors with pipelined instruction processing and multiprocessor systems. This is especially true for video processing systems.

What kind of graphic information is there

Graphical information can be presented in two forms: analog or discrete. By splitting a graphic image into a large number of small color fragments, graphic information is converted from analog to discrete form. In this case, encoding is performed-assigning each element of the image a specific value in the form of a code. The General scheme of digital image processing can be presented in the following order:

1. Getting the original image.

2. Filtering of the image.

3. Converting the image to the desired color model.

4. Formatting and indexing the image.

5. Splitting into blocks. Processing information contained in blocks.

6. The image compression.

This is the end of this article.

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