Title :
Medical Image Compression Using Ripplet Transform
Author :
Dhaarani, C. ; Venugopal, D. ; Raja, A. Sivanantha
Author_Institution :
Dept. of ECE, K.L.N Coll. of Inf. Technol., Madurai, India
Abstract :
Now-a-days the medical image compression plays a major role in the image processing. Even though the technology is improvised but still it needs the storage space and efficient bandwidth utilization. This paper presents the compression of grey scale medical images. The proposed method uses a new transform called Ripplet Transform, a higher dimensional generalization of the curvelet transform used to represent the images or two dimensional signals at different scales and different directions and Huffman algorithm to encode significant coefficients. The main goal of this method is to improve the compression ratio and to minimize the mean square error. From the experimental results obtained it is proved that the compression ratio and the peak to signal noise ratio is achieved high for various Medical images.
Keywords :
Huffman codes; curvelet transforms; data compression; image coding; mean square error methods; medical image processing; Huffman algorithm; bandwidth utilization; compression ratio; compression ratio improvement; curvelet transform; grey scale medical image compression; image processing; images represent; mean square error minimization; peak-to-signal noise ratio; ripplet transform; storage space; Biomedical imaging; Huffman coding; Image coding; Magnetic resonance imaging; PSNR; Wavelet transforms; Huffman algorithm; Medical image compression; compression ratio; mean square error; peak signal to noise ratio; ripplet transform;
Conference_Titel :
Intelligent Computing Applications (ICICA), 2014 International Conference on
Conference_Location :
Coimbatore
DOI :
10.1109/ICICA.2014.57