J. Today’s Ideas - Tomorrow’s Technol.

Image Compression using an efficient hybrid algorithm

Sandhya Sharma and Urvashi Bhat

  • Download PDF
  • DOI Number

Image compression, hybrid, quantization, DWT, DCT, CR, PSNR, MSE, Huffman encoding, medical image.

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[3]. 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[5]. 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[1]. 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[1]. 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

Page(s) 45-50
URL http://dspace.chitkara.edu.in/jspui/bitstream/1/228/1/11004_JOTITT_urvasi.pdf
ISSN Print : 2321-3906, Online : 2321-7146
DOI https://doi.org/10.15415/jotitt.2013.11004

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.

  • Sandhya Sharma and Sarabjeet Kaur,Image Compression using hybrid of DWT, DCT and Huffman Coding in “International Journal of Science and Emerging Technologies with Latest Trends” 5(1): 19-23 (2013)
  • Mahmoud A. Mofaddel et al, “Object based hybrid image and video coding scheme” IEEE 2011.
  • Aree Ali Mohammed, “Hybrid Transform coding scheme for medical image application ” IEEE2011.
  • XiHong ZHOU,” Research on DCT-base Image Compression Quality” Cross Strait Quad- Regional Radio Science and Wireless Technology Conference , IEEE 2011
  • Suchitra Shreshtha et al,”Hybrid DWT-DCT Algorithm for Biomedical image and video compression applications.” 10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010)IEEE, 2010.
  • Sunil Bhooshan,” An efficient and selective image compression scheme using Huffman and adaptive Interpolation” 24th International Conference Image and Vision Computing New Zealand (IVCNZ 2009) IEEE 2009
  • Chong Fu,” A DCT based Fractal Image Compression method” International workshop on chaos- fractals theories & Applications, IEEE 2009
  • Zhang Shi-qiang,” The image compression method based on adaptive segment and adaptive quantified ” The 3rd International Conference on Innovative Computing Information and control, IEEE 2008