APPLICATION OF METHODS OF AFFINITY TRANSFORMATION OF MATRIXES OF RASTER IMAGE PIXEL VALUES (2021)
The following goals were set within the scientific work: to create a method, an
algorithm and a program for compression of raster (pixel) graphic information using special
mathematical methods, or affine transformations. The main task was to provide a high degree of image compression with a minimum deterioration of image quality. An original method for replacing a large number of pixel blocks in the source image by a relatively small number of the most suitable specially created domain blocks was developed. Affine transformation consists in moving any domain block from a set to any part of the image, while ensuring maximum similarity of source and domain blocks.
To implement the method, an algorithm and a program in the modern and popular Python language have been developed. We have considered the example of image transformation in grayscale of 256x256 pixels using domain blocks created from 4x4 pixel image areas. The result is an image visually indistinguishable from the original image, which requires only 0.3125 of the original information to describe. Calculations were also performed with a smaller number of domain blocks.
The developed method and program proved a high degree of compression of bitmap images with preservation of their quality. It is possible to further improve the described algorithm and the program presented on the author’s site by simultaneous application of different types of affine transformations.
It is shown that the same method can be used not only for image processing, but also for the detection of similarity (fractal properties) in any flow of information.
Идентификаторы и классификаторы
The ever-increasing volume of data transmitted via various communication channels
requires improvement of compression methods.
Compression of different types of information (text, graphic, audio) is performed
using different algorithms. To achieve the highest degree of compression, it is often necessary
to make some losses of transmitted data. In this case it is desirable not to allow deterioration
of quality of “compressed material”; if deterioration of quality is unavoidable, it must affect
the perception of the most significant part of information as little as possible.
At present, the following types of lossless compression of graphic data are used [19]:
RLE, Huffman, LZW, and others. Unfortunately, all of them are characterized by low
compression of images of natural, photorealistic objects.
The best known method of image compression with losses is JPG (more correctly, it is
called a combination of methods chosen according to the required compression degree and the
resulting image quality). This method uses the psycho-physiological principles of human
perception of images: the components that are the least valuable for perception are discarded.
The main drawback of compression using JPG algorithms is the appearance of specific
unpleasant distortions (additional artifacts near lines and symbols) due to the so-called Gibbs
effect [11]. This effect is especially noticeable when processing drawings even at a low
compression rate.
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Выпуск
- A structural scheme for the origin and development of the Big Solar Cycle is proposed;
- We propose a simple explanation for inertial and non-inertial reference systems, inertial forces and inertial motion of bodies;
- Regularities of a production system development are discussed;
- Artificial acoustical impact inside natural clouds, in particular inside the non-precipitated stratiform clouds, non-precipitating shallow cumulus clouds, and Cu-clouds with drizzle, were analyzed;
- An original method for replacing a large number of pixel blocks in the source image by a relatively small number of the most suitable specially created domain blocks is developed;
- The problems associated with the disposal of different types of autonomous mobile robots are analyzed.
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Widespread introduction of mobile robotics in various spheres of human activity
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Издательство
- Издательство
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- Россия, Москва
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- 140080, Московская область, г. Лыткарино, ул. Парковая, Д. 1, офис 14/А
- ФИО
- Старцев Вадим Валерьевич (ГЕНЕРАЛЬНЫЙ ДИРЕКТОР)
- E-mail адрес
- systemology@yandex.ru
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