International Journal of Image, Graphics and Signal Processing(IJIGSP)
ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)
Published By: MECS Press
IJIGSP Vol.15, No.2, Apr. 2023
Investigation of Wavelets for Representation and Compression of Skin Cancer Images
Full Text (PDF, 694KB), PP.24-34
Wavelets play a key role in many applications like image representations and compression, which is a main issue in the process of reducing the size in bytes of a digital image file to store it in the memory and as well as to transmit. This paper presents image representation using various wavelet transforms. In the proposed method, the comparison between wavelets applied on an image are considered by counting the number of approximation coefficients retained for the representation of images and comparative analysis of the standard wavelets available is presented. This paper mainly aims at the type of the wavelet which retains less number of approximation coefficients for representing skin cancer image and gives the reduced compressed file size by considering the various parameters like Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity Index Measure (SSIM) and Compression Efficiency.
Cite This Paper
Pavithra D R, Sudarshan Patil Kulkarni, " Investigation of Wavelets for Representation and Compression of Skin Cancer Images", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.15, No.2, pp. 24-34, 2023. DOI:10.5815/ijigsp.2023.02.03
Gilbert Strang, Truong Nguyen, “Wavelets and Filter Banks”, Revised Edition, 1997
Ana Sovi´c, Damir Serˇsi´c, ” Adaptive Wavelet Image Decomposition using LAD Criterion”, 19th Europian Signal Processing Conference, (EUSIPCO 2011) Barcelona, Spain, pp.594-598, August - September 2, 2011
Pavithra D R, Sudarshan Patil Kulkarni, “A Review on Various Image Representation Techniques and Outcomes”, IJPRET, Vol 6 26-38, 2013
Khalid Sayood, “Introduction to data compression”, Fourth Edition, 2012.
S.G. Mallat, A theory for multi-resolution signal decomposition: the wavelet representation,IEEE Pattern Anal. Machine Intell. 11 (7) (1989) 674693.
Shivangi Jain, Vandana jagtap, Nitin Pise, “Computer aided Melanoma skin cancer detection using Image Processing”, International Conference on Intelligent Computing, Communication & Convergence, Proceedings Computer Science 48, 735 – 740, 2015.
Daubechies, “Image coding using wavelet transform”, IEEE Trans. on Image Proc., 1 (2):205-220, April 1992
Antonini M, Barlaud M, Mathieu P, Daubechies I. Image coding using wavelet transform. IEEE Tranactions on Image Processing
Fei Xiao, Yungang Zhang, “A Comparative study on Thresholding methods in Wavelet” Elsevier, Procedia Engineering 15
K S. Selvanayaki “Study and Analysis of wavelet based image compression techniques” International Journal of Image Processing and Vision Sciences (IJIPVS) ISSN(Print): 2278 – 1110, Vol-1 Iss-3,4 ,2012
N.S.A.M Taujuddin, Rosziati Ibrahim, Suhaila sari,”Wavelet coefficients reduction method based on standard deviation concept for high quality compressed image” Journal of Theoretical and Applied Information Technology, ISSN: 1992- 8645, Vol.79. No.3, 2015
Naveen kumar. R, B.N. Jagadale and J.S. Bhat, An Improved Image Compression Algorithm using Wavelet and Fractional Cosine Transforms, I.J. Image, Graphics and Signal Processing, 19-27, 2018
M. Vettereli and J. Kovaˇcevi´c, ‘Wavelets and sub-band Coding’, Prentice Hall, Englewood Cliffs, NJ, 1995.