Lossless Medical Image Compression by Integer Wavelet and Predictive Coding

Abstract

The future of healthcare delivery systems and telemedical applications will undergo a radical change due to the developments in wearable technologies, medical sensors, mobile computing, and communication techniques. When dealing with applications of collecting, sorting and transferring medical data from distant locations for performing remote medical collaborations and diagnosis we required to considered many parameters for telemedical application. E-health was born with the integration of networks and telecommunications. In recent years, healthcare systems rely on images acquired in two-dimensional domains in the case of still images or three-dimensional domains for volumetric video sequences and images. Images are acquired by many modalities including X-ray, magnetic resonance imaging, ultrasound, positron emission tomography, and computed axial tomography (Sapkal and Bairagi, 2011). Medical information is either in multidimensional or multiresolution form, which creates enormous amount of data. Retrieval, efficient storage, management, and transmission of these voluminous data are highly complex. One of the solutions to reduce this complex problem is to compress the medical data without any loss (i.e., lossless). Since the diagnostics capabilities are not compromised, this technique combines integer transforms and predictive coding to enhance the performance of lossless compression. The proposed techniques can be evaluated for performance using compression quality measures.

New Lossless Compression Method using Cyclic Reversible Low Contrast Mapping (CRLCM)

“…Recently, some researches in lossless compression methods commonly aim to optimize existing compression method for specific data type [7][8][9][10][11][12][13][14][15][16][17][18] or to improve the existing compression method by transforming data to other form before compression process or by combining several compression method [19][20][21][22]. One of novel researches in compression method is Asymmetric Numerical System (ANS) [23][24].…”

“…On this condition, the value of h is influenced by the rounding operation in (5). To restore the original value of x' and y', the new H value must be calculated using (9). This algorithm extracts the embedded bits (w) in the pair (x', y') and restore the original value (x, y).…”

New Lossless Compression Method using Cyclic Reversible Low Contrast Mapping (CRLCM)

“…Recently, some researches in lossless compression methods commonly aim to optimize existing compression method for specific data type [7][8][9][10][11][12][13][14][15][16][17][18] or to improve the existing compression method by transforming data to other form before compression process or by combining several compression method [19][20][21][22]. One of novel researches in compression method is Asymmetric Numerical System (ANS) [23][24].…”

“…On this condition, the value of h is influenced by the rounding operation in(5). To restore the original value of x' and y', the new H value must be calculated using(9). Dequeue the value of l. The number of bits are dequeued based on the RLCM properties on value of h. 6) Calculate the value of t using(10).…”

Region-Based Prediction and Quality Measurements for Medical Image Compression

“…Several image compression algorithms and hybrid techniques which combine neural networks [1], discrete wavelet transform (DWT), and predictive coding are still under research to achieve good compression ratio. A lossless predictive technique which combines existing prediction algorithms were also investigated [2].…”