Publication Type : Conference Paper, Journal
Publisher : IEEE
Source : Advances in Computer Applications
Url : https://ieeexplore.ieee.org/abstract/document/7887974
Campus : Coimbatore
School : School of Artificial Intelligence
Center : Center for Computational Engineering and Networking
Year : 2016
Abstract : This paper presents a novel image compression method for compressing medical images combining Haar-Wavelet Transform (HWT) and Residual Vector Quantization (RVQ) technique for enhancing the image quality and compression ratio. This method is used to represent an image in a compact form for reduced storage and efficient transmission. Nowadays, technology needs massive data transmission with low transmission cost. Image compression satisfies these requirements with reduced size of an image data by eliminating redundant information. Especially, medical field needs to store and access enormous image data for diagnosis. In this scenario, compression plays a vital part to store and transmit the data efficiently. The proposed method achieves high compression ratio without compromising the quality of reconstructed image.
Cite this Research Publication : Rani, M. Mary Shanthi, and P. Chitra. "A novel hybrid method of haar-wavelet and residual vector quantization for compressing medical images." In 2016 IEEE International Conference on Advances in Computer Applications (ICACA), pp. 321-326. IEEE, 2016.