Significance of Image Compression and Its Upshots - A Survey | Zendy

S. Boopathiraja | Zendy; P. Kalavathi | Zendy; C. Dhanalakshmi | Zendy

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Significance of Image Compression and Its Upshots - A Survey

Author(s) -

S. Boopathiraja,

P. Kalavathi,

C. Dhanalakshmi

Publication year - 2019

Publication title -

international journal of scientific research in computer science engineering and information technology

Language(s) - English

Resource type - Journals

ISSN - 2456-3307

DOI - 10.32628/cseit1952321

Subject(s) - lossy compression , lossless compression , image compression , computer science , image quality , data compression , peak signal to noise ratio , texture compression , color cell compression , data compression ratio , computer vision , artificial intelligence , compression ratio , image (mathematics) , image processing , engineering , internal combustion engine , automotive engineering

In the recent years, digital imaging and multimedia are comprising a large growth. It comes to practice that huge amount of image has been utilizing and it probably demand the image compression methods. Image compression is mainly used for reduce the storage size and transmission cost of an image. Based on the quality requirement, it is classified as either lossy or lossless. In this paper, we explore the significance of image compression and the upshot of the survey conducted from the image compression literature. Additionally, we review the various evaluation metrics for image compression such as Compression Ratio, Bit per Pixel, Mean Square Error, Peak Signal to Noise Ratio and Structural Similarity Index.

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