Implementation of Image Compression on Virtual Instrumentation Based Platform Using LabVIEW

Abhishek Shukla, Jyoti M.


In this digital era, the images are being stored or transmitted through the communication channel more often. The storage capacity and the bandwidth available for transmission are limited. To utilize storage capacity and the bandwidth effectively, it is necessary to convert the original image in an efficient compressed form. The objective of image compression is to reduce redundancy of the image data in order to store or transmit data in an efficient manner.

In this research work, the image compression is done by implementing DCT algorithm on Virtual Instrumentation based platform using LabVIEW. 


Image compression, discrete cosine transform (DCT), Virtual Instrumentation, LabVIEW

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Ghanbari M. Video Coding: An Introduction to Standard Codecs, IEE Press, 1999.

Richardson IEG. MPEG-4 and H.264 compression, Video Coding for Next-generation Multimedia, The Robert Gordon University, Aberdeen, UK.

Pennebaker WB, Mitchell JL, Fogg C et al. MPEG Digital Video Compression Standard, Chapman & Hall, 1997.

Jacobs M, Probell J. A Brief History of Video Coding, ARC International.

Kokaram A. Image Compression. Electronic and Electrical Engineering Dept.

Watson AB. Image Compression Using the Discrete Cosine Transform, NASA Ames Research Center.

Yamatani K, Saito N. Improvement of DCT-based Compression, Algorithms Using Poisson's Equation, Senior Member, IEEE.

Motion compensation, Intra prediction, Available at:


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