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Abstract
Image speaks more than words! We are dealing with images from Mars to Hollywood with a stop at the hospital. All of these images are compressed with the same amount of information while coming to us. So we need compression and in compression we need to deal with many transformations. Hence we will decide and choose the transformation which gives the best energy compaction. Energy compaction is the ability to pack energy of the spatial sequences into as few frequency coefficients as possible. It is important in image compression. If compaction is high, we only have to transmit a few coefficients instead of the whole set of pixels. So we will compare the result of all data of available many transformations. We will use MATLAB for the same.
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How to Cite
Kanaiyalal, P. K. (2014). Information Packing Ability of Transformations in Image Processing. International Journal of Emerging Trends in Science and Technology, 1(04). Retrieved from http://igmpublication.org/ijetst.in/index.php/ijetst/article/view/134
References
[1] “ A Comparative Study of Image Compression Techniques Based On Svd,Dwt-Svt,Dwt-Dctâ€,ICSCI2008
[2] R.C.Gonalez, R.E.Woods, S.L.Eddins,(2004), Digital Image Processing Using Matlab
[3] Mathematica Journal, (4)1, 1994, p.81-88 http://vision.arc.nasa.gov/ Image Compression
Using Discrete Cosine Transform,Andrew B.Waston publications/mathjournal94.pdf
[2] R.C.Gonalez, R.E.Woods, S.L.Eddins,(2004), Digital Image Processing Using Matlab
[3] Mathematica Journal, (4)1, 1994, p.81-88 http://vision.arc.nasa.gov/ Image Compression
Using Discrete Cosine Transform,Andrew B.Waston publications/mathjournal94.pdf