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Research on regional energy efficiency based on GIS technology and image quality processing
Economic development requires energy support, but the economy that relies too much on high energy consumption and high pollution is not sustainable. However, due to blind investment and low-level expansion of some new energy companies, some new energy industry has overcapacity and low production efficiency, slowing down the pace of new energy industry development, and limiting the development space of new energy companies. Thus, this paper is based on the GIS technology and image quality processing design improvement, around this idea, completed the new system simulation analysis, system development, experimental testing and so on. This paper focuses on the evaluation of the distribution efficiency of new energy industry based on image processing. Natural images have their own unique statistical properties, and interference can cause them to deviate from the original “natural statistical state.” According to the image itself and the characteristics of the human visual system, the expression of the image is adjusted, which is more conducive to the transmission, storage and understanding of information. Therefore, this paper proposes a new energy industry distribution efficiency evaluation method based on GIS technology and image processing from three aspects of the nature of natural images, the expression of image information and the characteristics of human visual system. The research shows that the method can objectively and effectively evaluate the distribution efficiency of the new energy industry, and has certain practicability, which can effectively alleviate the bottleneck problems faced above.
Research on regional energy efficiency based on GIS technology and image quality processing
Economic development requires energy support, but the economy that relies too much on high energy consumption and high pollution is not sustainable. However, due to blind investment and low-level expansion of some new energy companies, some new energy industry has overcapacity and low production efficiency, slowing down the pace of new energy industry development, and limiting the development space of new energy companies. Thus, this paper is based on the GIS technology and image quality processing design improvement, around this idea, completed the new system simulation analysis, system development, experimental testing and so on. This paper focuses on the evaluation of the distribution efficiency of new energy industry based on image processing. Natural images have their own unique statistical properties, and interference can cause them to deviate from the original “natural statistical state.” According to the image itself and the characteristics of the human visual system, the expression of the image is adjusted, which is more conducive to the transmission, storage and understanding of information. Therefore, this paper proposes a new energy industry distribution efficiency evaluation method based on GIS technology and image processing from three aspects of the nature of natural images, the expression of image information and the characteristics of human visual system. The research shows that the method can objectively and effectively evaluate the distribution efficiency of the new energy industry, and has certain practicability, which can effectively alleviate the bottleneck problems faced above.
Research on regional energy efficiency based on GIS technology and image quality processing
Chen, Zhuolun (Autor:in) / Wu, Xiaowei (Autor:in)
01.01.2019
Chen , Z & Wu , X 2019 , ' Research on regional energy efficiency based on GIS technology and image quality processing ' , Journal of Visual Communication and Image Representation , vol. 62 , pp. 410-417 . https://doi.org/10.1016/j.jvcir.2019.06.008
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
/dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy , SDG 7 - Affordable and Clean Energy , Model , SDG 8 - Decent Work and Economic Growth , /dk/atira/pure/sustainabledevelopmentgoals/decent_work_and_economic_growth , Deep learning , Quality , GIS technology , Image quality analysis
DDC:
690
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