Compression of image using multi-wavelet techniques

Document Type : Research Paper


1 Department of Computer Science, College of Computer Science and Information Technology, University of Basrah, Basrah, Iraq

2 Department of Information Systems, College of Computer Science and Information Technology, University of Basrah, Basrah, Iraq


Digital compression of images is a topic that has appeared in a lot of studies over the past decade to this day. As wavelet transform algorithms advance and procedures of quantization have helped to bypass current compression of image standards such as the JPEG algorithm. To get the highest effectiveness in compression of image transforms of wavelet need filters which gather a desirable character's number i.e., symmetry and orthogonally. Nevertheless, wave design capabilities are restricted due to their ability to have all of such desirable characters at the same time. The multi-wavelet technology removes a few of the restrictions of the wavelet play more than the options of design and thus able to gather all desired Characters of transforming. Wavelet and
multi-wave filter banks are tested on a larger scale with images, providing more useful analysis. Multiple waves indicate energy-compression efficiency (a higher compression ratio usually indicates a higher mean square error, MSE, in the compressed image). Filter bank Characters such as orthogonal and compact support, symmetry, and phase response are important factors that also affect MSE and professed quality of the image. The current work analyzes the multi-wave Characters effect on the performance of compression of images. Four multi-wavelength Characters (GHM, CL, ORT4) were used in this thesis and the compression of image performance of grayscale images was compared with common scalar waves (D4). SPIHT quantification device in stress chart and use of PSNR and subjective quality measures to assess performance. The results in this paper point out those multi wave characteristics that are most important for the compression of images. Moreover, PSNR results and subjective quality show similar performance to the best scalar and multi-waves. The analysis also shows that a programmer based on multi-band conversion significantly improves the perceived image quality.


[1] H. Abdul-Kareem, Video compression for communication and storage using wavelet transform and adaptive rood pattern search matching algorithm, Al-Mustansiriyah J. Sci. 24(5) (2013).
[2] A.A. Alhijaj and M. Kamil Hussein, Stereo images encryption by OSA & RSA algorithms, J. Phys. Conf. Ser. 1279(1) (2019).
[3] H.A. Ali and A.J.J.M.K. Hussein, Secure data hiding technique using video steganography, Des. Eng. 6 (2021) 6208–6217.
[4] J.A. Durlak, R.P. Weissberg, A.B. Dymnicki, R.D. Taylor and K.B. Schellinger, The impact of enhancing students’ social and emotional learning: A meta-analysis of school-based universal interventions, Child Dev. 82(1) (2011) 405–432.
[5] S.D. Hu, A novel video steganography based on non-uniform rectangular partition, 14th IEEE Int. Conf. Comput. Sci. Engin. 2011 pp. 57–61.
[6] M.K. Hussien, Encryption of stereo images after Estimated the motion using spatially dependent algorithms, Int. J. Comput. Sci. Mobile Comput. 5(12) (2016) 150–159.
[7] M.K. Hussien, Fast stereo images compression method based on wavelet transform and two dimensional logarithmic (TDL) algorithm, Glob. J. Comput. Sci. Technol. 17(2) (2017) 17–22.
[8] M.K. Hussien, Encryption of stereo images after compression by advanced encryption standard (AES), AlMustansiriyah J. Sci. 28(2) (2018) 156–161.
[9] M.K. Hussein, The optimum encryption method for image compressed by AES, Glob. J. Comput. Sci. Technol. 20(1) (2020) 17–24.
[10] M.K. Hussein, Voice cipher using Rc4 algorithm, 2020 Int. Conf. Elect. Commun. Comput. Engin. 2020 pp. 1–6.
[11] M.K. Hussien, Encryption of stereo images after compression by advanced encryption standard (AES), AlMustansiriyah J. Sci. 28(2) (2018) 156.
[12] M.K. Hussein, A.J. Jalil and A. Alhijaj, Face recognition using the basic components analysis algorithm, IOP Conf. Ser. Materials Sci. Engin. 928(3) (2020) 32010.
[13] M.K. Hussein, K.R. Hassan and H.M. Al-Mashhadi, The quality of image encryption techniques by reasoned logic, TELKOMNIKA 18(6) (2020) 2992–2998.
[14] M.K. Hussein and A. Alhijaj, TDL and Ron Rivest, Adi Shamir, and Leonard Adleman in Stereo images encrypt, J. Adv. Res. Dyn. Control Syst. 11(1 Special Issue) (2019) 1811–1817.
[15] M.K. Hussien and H.A.-K. Younis, Wavelet-based video compression system using diamond search (DS) matching algorithm, J. Kerbala Univ. 1 (2013) 249–258.
[16] M.K. Hussien and H.A.-K. Younis, DWT based-video compression using (4SS) matching algorithm, J. Univ. Hum. Dev. 1(4) (2015) 427–432.
[17] T. Hodgson, The Mechanics of Order: An Inquiry into the Utopian Possibilities of the Free and Open Source Ecology, Victoria University of Wellington, Masters Thesis, 2010.
[18] A.J. Jalil, Images recognition using eigenvectors based distributed features, Basrah J. Sci. 34(1) (2016) 1–10.
[19] L. Kohlberg and R. Mayer, Development as the aim of education, Harv. Educ. Rev. 42(4) (1972) 449–496.
[20] I. Khan, B. Verma, V.K. Chaudhari and I. Khan, Neural network based steganography algorithm for still images, INTERACT 2010 (2010) 46–51.
[21] J. Marshall, Learning with technology, Evid. that Technol. can, does, Support Learn. 2002.
[22] R. Palanivelu and P.S.S. Srinivasan, Safety and security measurement in industrial environment based on smart IOT technology based augmented data recognizing scheme, Comput. Commun. 150 (2020) 777–787.
[23] H.A. Younis and M.K. Hussein, Adaptive video compression technique based on wavelet and NTSS matching algorithm NTSS, J. College Educ. Pure Sci. 4(1) (2018) 203–214.
[24] H.A.-K. Younis and Z.A. Abbood, Steganography system to hide a sound file in a color image, J. THI-QAR Sci. 3(3) (2012).
Volume 13, Issue 1
March 2022
Pages 1519-1535
  • Receive Date: 08 October 2021
  • Revise Date: 08 September 2021
  • Accept Date: 25 November 2021