A REVIEW: MEDICAL IMAGE COMPRESSION TECHNIQUES

DEVENDRA KUMAR SHARMA, Navdeep Kaur Saluja

Abstract


Medical images are very important in the field of medicine. Every year, terabytes of medical image data are generated through advance imaging modalities such as magnetic resonance imaging (MRI), ultrasonography (US), computed tomography (CT), digital subtraction angiography (DSA), digital flurography (DF), positron emission tomography (PET), X-rays and many more recent techniques of medical imaging. But storing and transferring these huge voluminous data could be a tedious job. The digitization of the medical image information is of immense interest to the medical community which may lead to the implementation of e-health, teleradiology, tele-consultation, telemedicine and telematics. Discrete Cosine Transform (DCT) is one of the widely used compression method. Also the Discrete Wavelet Transform (DWT) provides substantial improvements in picture quality due to its multi resolution nature. Application of both methods together for image compression can provide a sustained Peak Signal to Noise Ratio (PSNR) along with a better overall compression ratio. In this paper a comparison of DCT & DWT in terms of Peak signal-to-noise ratio (PSNR), Mean Square Error (MSE) and overall Compression Ratio to illustrate the effectiveness of this method in Image compression.


Keywords


DCT (discrete cosine transform), DWT (discrete wavelet transform), MSE (mean square error), PSNR (peak signal to noise ratio), CR (compression ratio).

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References


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