Sandhya Sharma and Urvashi Bhat
Image compression, hybrid, quantization, DWT, DCT, CR, PSNR, MSE, Huffman encoding, medical image.
|PUBLISHED DATE||June 2013|
|PUBLISHER||The Author(s) 2013. This article is published with open access at www.chitkara.edu.in/publications|
This research paper proposes a method for the compression of medical images using an efficient hybrid algorithm. The objective of this hybrid (DWT,DCT and Huffman quantization) scheme is to calculate the compression ratio, peak signal to noise ratio and mean square error by changing the DWT level and Huffman quantization factor. The goal is to achieve higher compression ratio by applying different compression thresholds for the wavelet coefficient of each DWT band and then DCT with varying Huffman quantization factor while preserving the quality of reconstructed image. First DWT and DCT is applied on individual components RGB. After applying this image is quantized using Huffman quantization to calculate probability index for each unique quantity so as to find out the unique binary code for each unique symbol for their encoding.
Wavelet transform provides numerous desirable properties such as multi-resolution representation; scalability and progressive transmission which are beneficial to image compression applications as there is a need to handle lots of medical images in the hospitals. The amount of data produced by X-ray and CT scan techniques is vast and this might be a problem when sending the data over a network. To overcome this problem, image compression has been introduced in the field of medical. There have been numerous compression research studies, examining the use of compression as applied to medical images. To achieve higher degree of compression we have to choose the hybrid scheme of DWT, DCT and Huffman encoding compression technique. This paper proposes an approach to improve the performance of medical image compression while satisfying medical team who need to use it. There are several types of image compressions available but in case of biomedical images the loss of diagonasability of the image is not tolerable and hence to achieve higher degree of compression without any significant loss in the diagonasability of the image. An effective DWT algorithm has been performed on the RGB parts of the extracted input image separately. Once the DWT is performed on the image then next is to apply DCT by dividing the image into 60X60 blocks to make the components of frequency of the image which are greater than 60 as 0. After this histogram probability reduction function for all RGB components are calculated using Mean intensities. Then Image quantization is performed using ‘q’ factor which calculates probability index for each unique quantity. After applying quantization, Huffman code for each unique symbol is calculated so as to compress the image using Huffman compression. At the end the Compression ratio, Peak-signal-to-noise ratio and mean square error is calculated reducing the amount of data required to represent a given quantity of information
|ISSN||Print : 2321-3906, Online : 2321-7146|
In this paper a new hybrid scheme for medical image compression is proposed using hybrid of DWT, DCT and Huffman coding algorithm. This technique is tested against different medical images using different values of Huffman quantization factor. As the quantization factor increases the compression ratio increases and the quality measurement (PSNR) decreases.