Author
Listed:
- Megha Vaishnav
- Chandrashekhar Kamargaonkar
- Monisha Sharma
Abstract
Modern medical image diagnostic are often based on X-ray, computerized tomography and magnetic resonance imaging technique. The raw data delivered by such imaging devices more often than not take several mega-bytes of disk space. The diagnostic images for radiology interpretation must be efficiently stored and transmitted by physician for the further medical or legal purposes. Digital medical image processing generates large and data-rich electronics files. To speed up the electronic transmission and to minimize computer storage space, medical images are often compressed into files of smaller size. Compressed medical images have to protect all the original data details when they are restored for image presentation. The paper propose the dual tree wavelet transform and arithmetic coding technique of medical image compression. The dual-tree complex wavelet transform (CWT) is a relatively recent enhancement to the discrete wavelet transform (DWT), with important additional properties, it is nearly shift invariant and directionally selective in two and higher dimensions. And arithmetic coding is a common algorithm used in both lossless and lossy data compression algorithm. It protects all the key image information needed for the storage and transmission. Image compression is required to minimize the storage space and reduction of transmission cost.
Suggested Citation
Megha Vaishnav & Chandrashekhar Kamargaonkar & Monisha Sharma, 2017.
"Medical Image Compression Using Dual Tree Complex Wavelet Transform and Arithmetic Coding Technique,"
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 2(3), pages 172-176, June.
Handle:
RePEc:jbh:ijsrcs:v2:y2017:i3:id:hcseit172314
Note: Article URL: https://ijsrcseit.com/CSEIT172314
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jbh:ijsrcs:v2:y2017:i3:id:hcseit172314. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pankaj Sharma (USA) (email available below). General contact details of provider: https://ijsrcseit.com/home .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.