Review: ROI Based Medical Image Compression using DCT and HAAR Wavelet

Abstract

Image compression addresses the problem of reducing the amount of data required to represent a digital image. There are some areas of medicine where it is sufficient to maintain high image quality only for diagnostically significant regions, for example, tumor section of the brain MRI. This paper represents a compression method based on ROI and its performance analysis focusing on Discrete Cosine Transform technique. It is used for reducing the redundancy that is nothing but avoiding the replica data. The DCT is a mathematical function that transforms digital image data from the spatial domain to the frequency domain.

Mathematical Aspects of Laguerre Wavelets Transformation

“…The result of algorithms is a key to processing numbers or digital information, signals and images. Wavelet applications are data compression, fingerprints and many fields of science and engineering [5,7]. Wavelet image processing enables computers to store an image in many scales of resolutions.…”

Application of the Discrete Laguerre Wavelet Transform

“…This science has a very complex edge, it can be used in many fields such as medicine and military systems [3], [4]. Most of the studies in the field of image treatment have been used many types of waveforms known as Haar or other, which has many qualities that qualify them to use in this field [10]. The current work is different from references [5], [6] and [7], where the matrices used in image processing, larger dimensions, Arithmetic Peak Signal to Noise Ratio (PSNR), Mean Squared Error (MSE), which all were not discussed in the a f o r e m e n t i o n e d r e f e r e n c e s .…”