Abstract
When calculating the traditional image compression storage algorithm, the key frames of the video image are mainly extracted by the video image feature. In the process of video image acquisition, the influence of factors such as light is detected, and the image features are changed, resulting in a large storage problem. A new anti-noise compression storage algorithm for big data video images is proposed. First, the collected big data video images are divided. The average value of the gray of the image sub-region is obtained, and then the compression process and the stored procedure are given. The actual working effect of the algorithm is verified by comparison with the traditional algorithm. The experimental results show that the improved algorithm is well stored and the error is small. The fast anti-noise compression storage method for the big data video images studied in this paper has a good storage effect, and its application range is wider and more worthy of promotion.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Lei, T. (2019). Fast Anti-noise Compression Storage Algorithm for Big Data Video Images. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-030-36405-2_35
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DOI: https://doi.org/10.1007/978-3-030-36405-2_35
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