An Improved Image Compression-Decompression Technique Using Block Truncation and Wavelets

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Author(s)

Kuldeep Mander 1,* Himanshu. Jindal 2

1. Computer Science and Engineering Department, Bahra Group of Institutes, Patiala, Punjab, India – 147001

2. Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India – 147004

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2017.08.03

Received: 20 Mar. 2017 / Revised: 11 Apr. 2017 / Accepted: 8 May 2017 / Published: 8 Aug. 2017

Index Terms

Compression, BTC (Block Truncation Coding), DWT (Discrete Wavelet Transform), Interpolation, Spline, Contrast

Abstract

In the modern world, digital images play a vital role in a number of applications such as medical field, aerospace and satellite imaging, underwater imaging, etc. These applications use and produce a large number of digital images. Also, these images need to be stored and transmitted for various purposes. Thus, to overcome this problem of storage while transmitting these images, a process is used, namely, compression. The paper focuses on a compression technique known as Block Truncation Coding (BTC) as it helps in reducing the size of the image so that it takes less space in memory and easy to transmit. Thus, BTC is used to compress grayscale images. After compression, Discrete Wavelet Transform (DWT) with spline interpolation is applied to reconstruct the images. The process is suggested in order to view the changed pixels of images after compression of two images. The wavelets and interpolations provide enhanced compressed images that follow the steps for its encoding and decoding processes. The performance of the proposed method is measured by calculating the PSNR values and on comparing the proposed technique with the existing ones, it has been discovered that the proposed method outperforms the most common existing techniques and provides 49% better results in comparison with existing techniques.

Cite This Paper

Kuldeep Mander, Himanshu. Jindal,"An Improved Image Compression-Decompression Technique Using Block Truncation and Wavelets", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.9, No.8, pp.17-29, 2017. DOI: 10.5815/ijigsp.2017.08.03

Reference

[1]A. K. Katharotiya, S. Patel, and M. Goyani, “Comparative Analysis between DCT & DWT Techniques of Image Compression”, Journal of Information Engineering and Applications, Vol. 1, No.2, 2011.

[2]A. Kaur, and J. Kaur, “Comparison of DCT and DWT of Image Compression Techniques”, International Journal of Engineering Research and Development, vol. 1, Issue 4, pp. 49-52, 2012.

[3]A. Kaushik, and M. Gupta, “Analysis of Image Compression Algorithms”, International Journal of Engineering Research and Application, 2012.

[4]A. Sinha, M. Kumar, A. K. Jaiswal, and R. Sexena, “Performance Analysis Of High Resolution Images Using Interpolation Techniques in Multimedia Communication System”, Signal & Image Processing: An International Journal, Vol. 5, Issue 2,2014.

[5]B. S. Kumar, and S. Nagaraj, “Discrete and Stationary Wavelet Decomposition for Image Resolution Enhancement”, International Journal of Engineering Trends and Technology (IJETT), Vol. 4, Issue 7, 2013.

[6]C. Sun, S. J. Ruan, M. C. Shie, and T. W. Pai, “Dynamic Contrast Enhancement based on Histogram Specification”, IEEE Transactions on Consumer Electronics, Vol. 51, No. 4, pp.1300-1305, 2005.

[7]G. M. Padmaja, and C. H. R. Lakshmi, “Analysis of Various Image Compression Techniques”, International Journal of Reviews in Computing, 2012.

[8]G. Rompani, “Warped Distance for Space Variant Linear Image Interpolation”, IEEE Transactions of Image Processing, Vol. 8, Issue 5,1999.

[9]H. Huang, C. Cui, L. Cheng, Q. Liu, and J. Wang, “Grid Interpolation Algorithm Based On Nearest Neighbor Fast Search”, Springer, 2012.

[10]Hitashi, and G. Kaur, and S. Sharma, “Fractal Image Compression–A Review”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 2, No. 2, 2012.

[11]M. Kaur, and G. Kaur, “A Survey of Lossless and Lossy Image Compression Technique”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, Issue 2, 2013.

[12]M. Tonge, P. K. Malviya, and A. Gupta, “Implementation of Digital Watermarking Algorithm based on DWT and DCT”, International Journal of Advanced Engineering and Global Technology, Vol. 2, Issue 1, 2014.

[13]Md. F. Hossain, and M.R. Alsharif, “Image Enhancement Based on Logarithmic Transform Coefficient and Adaptive Histogram Equalization”, IEEE International Conference on Convergence Information Technology, 2007. 

[14]R. Olivier, and C. Hanqiang, “Nearest Neighbor Value Interpolation”, International Journal of Advanced Computer Science and Application”, Vol. 3, Issue 4, 2012.

[15]Z. Min, W. Jiechao, L. Zhiwei and, L. Yonghua, “An Adaptive Image Zooming Method with Edge Enhancement”, 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE), pp. 608-611, 2010.