Spectral image compression

Alexander L. Timofeev; Albert Kh. Sultanov; Ivan K. Meshkov; Azat R. Gizatulin

doi:10.1117/12.2632146

25 July 2022 Spectral image compression

Alexander L. Timofeev, Albert Kh. Sultanov, Ivan K. Meshkov, Azat R. Gizatulin

Proceedings Volume 12295, Optical Technologies for Telecommunications 2021; 122950V (2022) https://doi.org/10.1117/12.2632146
Event: Nineteenth International Scientific and Technical Conference "Optical Technologies for Communications", 2021, Samara, Russian Federation

Abstract

In this paper we present an effective and simple method of image compression based on spectral analysis rather than redundancy reduction. A significant portion of traffic transmitted over communication channels is static and dynamic images, and the volume of this traffic is growing at a faster rate than the capacity of communication channels is increasing. One of the ways to solve this problem is to compress the transmitted images. Data compression can be done in two ways – with and without loss of information. A distinctive feature of images as a form of information presentation is the presence of large internal redundancy, which allows the use of lossy compression methods. To exclude the loss of meaningful information, it is necessary to take into account the specifics of specific signals and divide them into groups according to the predominant concentration of information in the frequency or in spatial domain. To do this, one can use the analysis of the spatial spectrum of images and remove some part of the spectrum with an acceptable loss of information.

Citation Download Citation

Alexander L. Timofeev, Albert Kh. Sultanov, Ivan K. Meshkov, and Azat R. Gizatulin "Spectral image compression", Proc. SPIE 12295, Optical Technologies for Telecommunications 2021, 122950V (25 July 2022); https://doi.org/10.1117/12.2632146

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KEYWORDS

Image compression

Computer programming

Image processing

Quantization

Image quality

Image transmission

Digital image processing

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