High Quality Color Image Compression for Discrete Transform Domain Downward Conversion Block Based Image Coding | Zendy

Deepak Gupta | Zendy; Neetesh Gupta | Zendy

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High 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 (ijrte)

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 , color cell compression , block truncation coding , data compression ratio , peak signal to noise ratio , image quality , algorithm , computer vision , artificial intelligence , image processing , 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.

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