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Year : 2011  |  Volume : 2  |  Issue : 3  |  Page : 123  

Comparison of the DCT JPEG and wavelet image compression encoder for medical images


Section of Computer Engineering, University Polytechnic, Faculty of Engineering and Technology, Jamia Millia Islamia (A Central University), New Delhi-110025, India

Date of Web Publication26-May-2012

Correspondence Address:
Farah Jamal Ansari
Section of Computer Engineering, University Polytechnic, Faculty of Engineering and Technology, Jamia Millia Islamia (A Central University), New Delhi-110025
India
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Source of Support: None, Conflict of Interest: None


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How to cite this article:
Ansari FJ, Ali A. Comparison of the DCT JPEG and wavelet image compression encoder for medical images. J Nat Sc Biol Med 2011;2, Suppl S1:123

How to cite this URL:
Ansari FJ, Ali A. Comparison of the DCT JPEG and wavelet image compression encoder for medical images. J Nat Sc Biol Med [serial online] 2011 [cited 2020 Feb 24];2, Suppl S1:123. Available from: http://www.jnsbm.org/text.asp?2011/2/3/123/96241

X rays were invented by the German physicist Wilhelm Ontgen (1845-1923), also for which he received the first Nobel Prize in Physics in 1901. Since then X-rays are used for seeing the inside of a human body. Usually the size of a digital chest X-ray is 2000 x 2500 pixels with bits/pixel ratio being 12. Such kind of images takes 10 megabytes for storage. Generally every hospital needs to assign a storage space of 5 Terabytes to 15 Terabytes for storing X-ray type of images. Also a very fast network is required to move the images within the X-ray department. This increasing volume in the data generated by medical equipments gave rise to different compression techniques to decrease the storage space and also to give access to faster movement of images on the network. The most promising of the compression standards available are jpeg compression and wavelet compression. This paper summarizes on the comparison between the two compression methods based on compression ratio and compression quality for medical images. In JPEG technique an input image is divided into 8*8 blocks. Each block is further changed into the frequency domain with the help of the Discrete Cosine transform, quantized using default quantization matrix and further compressed by using entropy encoding. Wavelet transform image compression is a new field of applied mathematics often called the 'wavelet theory' or "wavelets". Wavelet compression is one of the techniques of "transform-based compression". The first step in every transform-based technique is a lossless mathematical transformation to provide a sparse representation of an input image. The transformed data are then quantized, in order to achieve the desired level of compression.Although JPEG is clinically supported by DICOM but its biggest disadvantage is that it introduces artifacts resulting from the block-based DCT scheme. Both the methods give the same kind of results till a compression ratio of 30:1. Jpeg compression gives good results till a compression ratio of 30:1. After this the quality of the picture starts to degrade. Wavelet- based coding tends to give substantial good results at higher compression ratios. Wavelet compression gives a very high compression ratio of 600:1. JPEG2000 also uses wavelet coding for compressing its images. Wavelet compression leads to better compression ratios and picture quality.




 

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