International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 139 - Number 4 |
Year of Publication: 2016 |
Authors: Aman Utkarsh, Chandralika Chakraborty |
10.5120/ijca2016909145 |
Aman Utkarsh, Chandralika Chakraborty . Image Compression: A Comparative Study between ANN and Traditional Approach. International Journal of Computer Applications. 139, 4 ( April 2016), 27-30. DOI=10.5120/ijca2016909145
Image compression is a highly essential part of image processing and is a necessity of the modern world required in various fields. It is a process of representing image data using fewer bits than it is required for the original, by performing image compression a certain amount of data used by the image for its storage can be reduced. Compression is necessary in cases where a large amount of data is to be stored or transferred. This paper reviews some of the conventional methods for achieving Image compression, viz. Run length encoding, DCT, DWT to name a few. Artificial neural networks can also be used to achieve image compression. Here, an attempt is made to compare between the traditional methods of performing image compression and the artificial neural network approach.