1. Miheer Gurjar, Prashant Jagannathan, “Image Compression: Review and Comparsion of Haar Wavelet Transform and Vector Quantization”, 2003.
  2. The Internet Encyclopedia, http://en.Wikipedia.org/wiki/Haar
  3. Kamrul Hasan Talukder and Koichi Harada, “Haar Wavelet Based Approach for Image Compression and Quality Assessment of Compressed Image”, 2007.
  4. Csabo Petre, Vineet Varma,“Wavelet Image Compression on the DSP”, 2007.
  5. Bushra K. Al-Abudi and Loay A. George, “Color Image Compression Using Wavelet Transform”, College of Science, University of Baghdad-Iraq, 2005.
  1. Satish Kumar, Kanwarinder Singh, “Image Compression using Discrete Wavelet Transform by Haar Tehnique.
  2. Myung-Sin Song, “Wavelet Image Compression”, Southern Illinois University Edwardsville, Edwardsville, IL62026, USA, 2004.
  3. Ashkan Olyaei, Roman Genov, “Mixed-Signal CMOS Wavelet Compression Imager Architecture”, 2005.


Tikrit Journal of Engineering Sciences (2011) 18(2) 88- 101

Image Compression using Haar and Modified Haar Wavelet Transform

Mohannad Abid Shehab Ahmed
Haithem Abd Al-Raheem Taha
Musab Tahseen Salah Aldeen
Electrical Eng. Dept.- Al-Mustansirya University, Iraq


Efficient image compression approaches can provide the best solutions to the recent growth of the data intensive and multimedia based applications. As presented in many papers the Haar matrix–based methods and wavelet analysis can be used in various areas of image processing such as edge detection, preserving, smoothing or filtering. In this paper, color image compression analysis and synthesis based on Haar and modified Haar is presented. The standard Haar wavelet transformation with N=2 is composed of a sequence of low-pass and high-pass filters, known as a filter bank, the vertical and horizontal Haar filters are composed to construct four 2-dimensional filters, such filters applied directly to the image to speed up the implementation of the Haar wavelet transform. Modified Haar technique is studied and implemented for odd based numbers i.e. (N=3 & N=5) to generate many solution sets, these sets are tested using the energy function or numerical method to get the optimum one.
The Haar transform is simple, efficient in memory usage due to high zero value spread (it can use sparse principle), and exactly reversible without the edge effects as compared to DCT (Discrete Cosine Transform). The implemented Matlab simulation results prove the effectiveness of DWT (Discrete Wave Transform) algorithms based on Haar and Modified Haar techniques in attaining an efficient compression ratio (C.R), achieving higher peak signal to noise ratio (PSNR), and the resulting images are of much smoother as compared to standard JPEG especially for high C.R.
A comparison between standard JPEG, Haar, and Modified Haar techniques is done finally, which approves the highest capability of Modified Haar between others

Download Full-text PDF

Keywords: Discrete Wavelet Transform, Haar, Modified Haar, Linear Matrix Algebra, Sparse matrix.

How to cite

TJES: Ahmed MAS, Taha HAA, Salah Aldeen MT, Image Compression using Haar and Modified Haar Wavelet Transform. Tikrit Journal of Engineering Sciences 2011; 18(2): 88-101
APA: Ahmed, M.A.S, Taha, H.A.A, Salah Aldeen M.T., (2011). Image Compression using Haar and Modified Haar Wavelet Transform. Tikrit Journal of Engineering Sciences, 18(2), 88-101.

Loader Loading...
EAD Logo Taking too long?
Reload Reload document
| Open Open in new tab

Download [864.01 KB]