The system for processing graphic images using the Floyd-Steinberg algorithm has been developed. The developed system helps to smooth images when displayed on devices with different resolutions and different sets of color palettes. Due to the application of the Floyd-Steinberg algorithm, the processed images have minimal distortion during their reproduction. The proposed algorithm can be used to compress and transmit images and audio signals. The system is designed using the Java Processing language.
In this article, we present a new algorithm for digital image processing noised by mixed Gaussian-impulse noise. Our mathematical model is based on the divide-conquer technique coupled with a reaction-diffusion system. We first decompose our image into low and high-frequency components by convolving each with a predefined convolutional filter. Further, we use a simple scheme of different weights to integrate and collect these processed sub-images into a filtered image. Finally, we apply our Reaction-Diffusion system to increase the contrast in the image. A number of experimental result
The aim of the work is to develop an automated measuring system in a mechanical gyrocompass with the help of specially developed hardware and software in order to facilitate the operation of the device and minimize observer errors. The developed complex provides automation only for the time method, as for the method of the turning point it is necessary to constantly contact the motion screw of the total station. The project is based on an integrated system, the hardware part of which contains a single-board computer, camera, and lens.
In the research a method for segmentation of partially-blurred images using the wavelet transformation, particularly coiflet of the order L=3 is presented. The entropy is used as a segmentation criterion based on wallet transformation. K-means method is used for image segmentation. Developed method was tested and has shown good results of his work; it correctly performs more than 82 % of pixels of image, and in many individual cases, more than 90 %.
Current approach to the increase of the resolution is based on receiving images from several image sensor arrays shifted by subpixel distance [1, 2]. The analysis of the image forming process has shown that a pixel aperture works as a low-pass spatial filter and decreases spatial resolution even if several image sensors shifted by subpixel distance are used. The proposed by the authors approach uses both shifted image sensor arrays and data processing based on inverse filtering.
The article deals with the factors affecting the quality of formation and resolution of an image in a high-resolution scanner (HRS). It is shown that the stabilization parameters of a spacecraft (SC), on which a HRS with a charge-coupled device operating in time delay integration mode (TDI-CCD) is installed, significantly affect an image distortion, namely its blurring, and this blurring increases when the number of integration lines goes up in the TDI sensor.
This paper is devoted to considering of ways to improve the resolution, principles and methods of subpixel imaging technology, assessment of the development status and the latest research developments. Modern approaches to improving the spatial resolution as the main parameter of satellite images are based on algorithmic search and design solutions as the technology of manufacturing image sensors exhaust its potential for improvement. One of the major tasks of remote monitoring is to improve the quality of images, which is determined by parameters such as resolution.
The methods, their advantages and disadvantages, of fusion a low-resolution multispectral and panchromatic high-resolution image in high-resolution color image are considered. Is proposed a method to provide high-resolution, which is based on the use of sub-pixel processing, the essence of which is the handling of input data in the form of a CCD sensor arrays shifted by a half pixel with respect to each other.