Open AccessA New Proposed Method For A Statistical Rules-Based Digital Image Compression
Author(s) -
Khadhim Mahdi Hashim,
Salwa Shakir Baawi,
Bushra Kamil Hilal
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1897/1/012067
Subject(s) - lossy compression , image compression , data compression , peak signal to noise ratio , color cell compression , data compression ratio , compression ratio , computer science , lossless compression , redundancy (engineering) , texture compression , artificial intelligence , image quality , pixel , compression (physics) , computer vision , image (mathematics) , image processing , engineering , materials science , composite material , internal combustion engine , automotive engineering , operating system
Image compression depends on data compression of digital images. Its central objective is to decrease the redundancy of the image data for reducing space and the cost of transmitting data in public communication channels. This research suggests a new compression technique based on the statistical rules. The proposed technique is one of the lossy compression techniques is based upon the statistics of the pixel values of the gray-scale image. The quality of these compressed images have been evaluated using some factors like the Image size before/after the compression process, Compression Ratio, (CR), and Peak Signal to Noise Ratio, (PSNR), Mean Square Error (MSE), and Mean Space Saving (MSS). Experimental results have demonstrated that the proposed technique provides sufficient higher compression with minimal to lose data.