REPro.JPEG: a new image compression approach based on reduction/expansion image and JPEG compression for dermatological medical images

ABSTRACT Medical images are known for their huge volume which becomes a real problem for their archiving or transmission notably for telemedicine applications. In this context, we present a new method for medical image compression which combines image definition resizing and JPEG compression. We baptise this new protocol REPro.JPEG (reduction/expansion protocol combined with JPEG compression). At first, the image is reduced then compressed before its archiving or transmission. At last, the user or the receiver decompresses the image then enlarges it before its display. The obtain results prove that, at the same number of bits per pixel lower than 0.42, that REPRo.JPEG guarantees a better preservation of image quality compared to the JPEG compression for dermatological medical images. Besides, applying the REPRo.JPEG on these colour medical images is more efficient while using the HSV colour space compared to the use of RGB or YCbCr colour spaces.

[1]  L. Rabiner,et al.  A digital signal processing approach to interpolation , 1973 .

[2]  E. Maeland.  On the comparison of interpolation methods. , 1988, IEEE transactions on medical imaging.

[3]  M. Unser,et al.  Interpolation revisited [medical images application] , 2000, IEEE Transactions on Medical Imaging.

[4]  Frank Y. Shih,et al.  Robust watermarking and compression for medical images based on genetic algorithms , 2005, Inf. Sci..

[5]  Mohamed KALLEL,et al.  Use of Multi-Watermarking Schema to Maintain Awareness in a Teleneurology Diagnosis Platform , 2010 .

[6]  Chun Kiat Tan,et al.  Security Protection of DICOM Medical Images Using Dual-Layer Reversible Watermarking with Tamper Detection Capability , 2011, Journal of Digital Imaging.

[7]  Antonio Plaza,et al.  Graphics processing unit implementation of JPEG2000 for hyperspectral image compression , 2012 .

[8]  Ali Khalfallah,et al.  Image encryption with dynamic chaotic Look-Up Table , 2012, 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT).

[9]  M. S. Bouhlel,et al.  New method for analysis of fluorescent microscopy images dedicated to the description of the dynamics chromosome , 2012, 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT).

[10]  Yuvraj Sharma,et al.  Comparison Of Different Image Enhancement Techniques Based Upon Psnr & Mse , 2012 .

[11]  A. Khalfallah,et al.  Evaluation of image fusion techniques in nuclear medicine , 2012, 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT).

[12]  A. Khenchaf,et al.  Segmentation of radar images using a combined watershed and Fisher techniques , 2012, 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT).

[13]  Bruno Carpentieri,et al.  A Secure Low Complexity Approach for Compression and Transmission of 3-D Medical Images , 2013, 2013 Eighth International Conference on Broadband and Wireless Computing, Communication and Applications.

[14]  S. Bhavani,et al.  Comparison of fractal coding methods for medical image compression , 2013, IET Image Process..

[15]  Jonathan Loo,et al.  A novel low complexity Local Hybrid Pseudo-SSIM-SATD distortion metric towards perceptual rate control , 2013, 2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB).

[16]  Jean-Christophe Lapayre,et al.  A Tool for Telediagnosis of Cardiovascular Diseases in a Collaborative and Adaptive Approach , 2013, J. Univers. Comput. Sci..

[17]  Jean-Christophe Lapayre,et al.  Scars collaborative telediagnosis platform using adaptive image flow , 2013, Integr. Comput. Aided Eng..

[18]  Gwanggil Jeon.  YCbCr Image Supported NIR Image Enhancement , 2014, MUE 2014.

[19]  Roman Starosolski,et al.  New simple and efficient color space transformations for lossless image compression , 2014, J. Vis. Commun. Image Represent..

[20]  Ali Khalfallah,et al.  A new Watermarking Technique for Medical Image using Hierarchical Encryption , 2014, ArXiv.

[21]  Nan Jiang,et al.  Quantum image scaling using nearest neighbor interpolation , 2015, Quantum Inf. Process..

[22]  Jean-Christophe Lapayre,et al.  REPRO: A NEW REDUCTION/EXPANSION PROTOCOL TO INCREASE THE PERFORMANCE OF IMAGE TRANSMISSION IN MEDICAL TELEDIAGNOSIS PLATFORMS , 2015 .

[23]  Michael W. Marcellin,et al.  Compression Based on a Joint Task-Specific Information Metric , 2015, 2015 Data Compression Conference.

[24]  Alfredo De Santis,et al.  Cloud-based adaptive compression and secure management services for 3D healthcare data , 2015, Future Gener. Comput. Syst..

[25]  Muhammad N. Marsono,et al.  2-D DWT System Architecture for Image Compression , 2015, J. Signal Process. Syst..

[26]  Young Shik Moon,et al.  Super-Resolution Image Reconstruction Using Wavelet Based Patch and Discrete Wavelet Transform , 2015, J. Signal Process. Syst..

[27]  Peter Schelkens,et al.  Wavelet based volumetric medical image compression , 2015, Signal Process. Image Commun..

[28]  Armando J. Pinho,et al.  Progressive Lossy-to-Lossless Compression of DNA Microarray Images , 2016, IEEE Signal Processing Letters.

[29]  Marykutty Cyriac,et al.  An object-based lossless compression approach for medical images using DPCM , 2016, Int. J. Bioinform. Res. Appl..

[30]  Yen-Tai Lai,et al.  A High-Throughput JPEG XR Encoder , 2016, J. Signal Process. Syst..

[31]  Ali Khalfallah,et al.  A Chaotic Cryptosystem for Color Image with Dynamic Look-Up Table , 2016, ICISP.

[32]  Med Salim Bouhlel,et al.  Using ROI with ISOM compression to medical image , 2016, Int. J. Comput. Vis. Robotics.

[33]  Ali Khalfallah,et al.  Watermarking for Improving the Reduction-Expansion Process of Medical Images (WREPro) , 2016 .

[34]  Abhishek Kumar,et al.  An innovative DNA cryptography technique for secure data transmission , 2016, Int. J. Bioinform. Res. Appl..

[35]  Jean-Christophe Lapayre,et al.  Medical Image Compression Approach Based on Image Resizing, Digital Watermarking and Lossless Compression , 2017, J. Signal Process. Syst..

[36]  Harpreet Kaur,et al.  Comparison on Different Image Enhancement Techniques , 2017 .