Open AccessHigh Quality Color Image Compression for Discrete Transform Domain Downward Conversion Block Based Image Coding
Author(s) -
Deepak Gupta,
Neetesh Gupta
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d7131.118419
Subject(s) - uncompressed video , computer science , image compression , data compression , context adaptive binary arithmetic coding , block truncation coding , color cell compression , peak signal to noise ratio , data compression ratio , image quality , algorithm , computer vision , image processing , artificial intelligence , computer engineering , image (mathematics) , video processing , video tracking
Text and image data are important elements for information processing almost in all the computer applications. Uncompressed image or text data require high transmission bandwidth and significant storage capacity. Designing and compression scheme is more critical with the recent growth of computer applications. Among the various spatial domain image compression techniques, multi-level Block partition Coding (MLBTC) is one of the best methods which has the least computational complexity. The parameters such as Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are measured and it is found that the implemented methods of BTC are superior to the traditional BTC. This paves the way for a nearly error free and compressed transmission of the images through the communication channel.