Lopukhova, E.; Voronkov, G.; Kuznetsov, I.; Ivanov, V.; Kutluyarov, R.; Grakhova, E. A Novel Energy-Efficient Coding Based on Coordinated Group Signal Transformation for Image Compression in Energy-Starved Systems. Appl. Sci.2024, 14, 4176.
Lopukhova, E.; Voronkov, G.; Kuznetsov, I.; Ivanov, V.; Kutluyarov, R.; Grakhova, E. A Novel Energy-Efficient Coding Based on Coordinated Group Signal Transformation for Image Compression in Energy-Starved Systems. Appl. Sci. 2024, 14, 4176.
Lopukhova, E.; Voronkov, G.; Kuznetsov, I.; Ivanov, V.; Kutluyarov, R.; Grakhova, E. A Novel Energy-Efficient Coding Based on Coordinated Group Signal Transformation for Image Compression in Energy-Starved Systems. Appl. Sci.2024, 14, 4176.
Lopukhova, E.; Voronkov, G.; Kuznetsov, I.; Ivanov, V.; Kutluyarov, R.; Grakhova, E. A Novel Energy-Efficient Coding Based on Coordinated Group Signal Transformation for Image Compression in Energy-Starved Systems. Appl. Sci. 2024, 14, 4176.
Abstract
The paper describes the new method for image compression based on coordinated group signal transformation. The algorithm is a type of difference coding. Coordinated processing significantly simplifies the difference signal conversion scheme using a single group codec for all signals. The described method considers color channels as correlated signals of a multi-channel communication system. The specifics of the processed data required modification of the coordinated group processing algorithm. First, we changed how to calculate the difference signals to prevent data loss. Secondly, the group codec was supplemented with a neural network to improve the quality of reconstructed images. We considered the following types of neural networks: fully connected, recurrent, convolution, and convolution in the Fourier space. Based on the simulation results, it is best to use fully connected neural networks if the goal is to minimize processing delay time. These networks have a response time of 13 ms. On the other hand, if the priority is to improve quality in cases where delays are not critical, then convolution neural networks in the Fourier space should be used. These networks have a response time of 140 ms and are of significant interest.
Keywords
energy-efficient coding; differential coding; coordinated group signal transformation; image compression; image quality criteria; neural networks
Subject
Engineering, Telecommunications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
