Color Image Compression using hybrid Haar-DCT wavelet in Different color spaces
DOI:
https://doi.org/10.14738/aivp.24.371Keywords:
Image compression, Hybrid Wavelet Transform, SSIM, AFCPVAbstract
This paper compares digital image compression in various color spaces using Hybrid Haar wavelet transform. As DCT has high energy compaction property, it is combined with Haar transform generating Haar-DCT hybrid wavelet transform. Different component sizes are used and error at different compression ratios up to 32 is observed. At higher compression ratios 16-16 component pair gives minimum error. This pair is further used to compress images in different color spaces like RGB, KLUV, YUV, YIQ, XYZ and YCbCr. KLUV color space show considerably less Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) than other color spaces. Average Fractional Change in Pixel Value (AFCPV) in KLUV color space is nearly half than other color spaces. RMSE, MAE these measures are not sufficient as it give perceived error to human visual system. Hence other error metric Structural Similarity Index (SSIM) is used to observe performance superiority of various color spaces. SSIM in KLUV and RGB color space is equal having value 0.994 which is closest to one indicating better but similar image quality in both color spaces. This observation cannot be emphasized using traditional error metrics like RMSE, MAE and AFCPV.
References
Strang G. "Wavelet Transforms Versus Fourier Transforms." Bull. Amer. Math. Soc. 28, 1993, 288-305.
N. Ahmed, T. Natarajan and K. R. Rao, “Discrete Cosine Transform”, IEEE Transaction Computers, January 1974, C-23, pp. 90-93.
S. Mallat, "A Theory of Multiresolution Signal Decomposition: The Wavelet Representation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, pp. 674-693, 1989.
M.S. Abdullah, N. Subba Rao, “Image Compression using Classical and Lifting based Wavelets”, International Journal of Advanced Research in Computer and Communication Engineering, August 2013, Vol. 2, Issue 8, pp. 3193-3198.
Daubechies, I. “The wavelet transform, time-frequency localization and Signal analysis”, IEEE Transformation and Information Theory 36: 1990, 961-1005.
Wei-Pin Lin, Chih-Ming Chen, and Yung-Chang Chen, “Image Compression with Interpolation in Wavelet Transform Domain” 2005. IEEE International Symposium on Circuits and Systems (ISCAS), 2005, Vol. 3, pp. 2084 – 2087.
Jose Oliver, Manuel P. Malumbres, “Low Complexity Multi-Resolution Image Compression using Wavelet Lower Trees”, IEEE Trans. on Circuits and Systems for Video Technology, Nov. 2006, Vol. 16, Issue 11, pp. 1437-1444.
Maleki A, Rajaei B, Pourreza H.R., “Rate Distortion Analysis of Directional Wavelets”, IEEE Trans. on Image Processing, Feb 2012, Vol. 21 Issue 2, pp. 588-600.
Shih-Chung B. Lo, Huai Li, and Matthew T. Freedman, “Optimization of Wavelet Decomposition for Image Compression and Feature Preservation”, IEEE Trans. on Medical Imaging, Vol. 22, Issue 9, Sept 2013, pp. 1141-1151.
E. Elharar, Adrian Stern, Ofer Hadar, and Bahram Javidi, “A Hybrid Compression Method for Integral Images using Discrete Wavelet Transform and Discrete Cosine Transform”, Journal Of Display Technology, September 2007, Vol. 3, No. 3, pp. 321-325.
Jingyu Yang, Wenli Xu, Qionghai Dai, Yao Wang, “Image Compression using 2D Dual Tree Discrete Wavelet Transform (DDWT)”, IEEE International Symposium on Circuits and Systems, May 2007, pp. 297-300.
Xiao-Yan Xu, Chen, P., Juan Dai, “Hybrid Encoding Analysis of Fractal Image Compression Method Based on Wavelet Transform”, In Proc of International Conference of Machine Learning and Cybernetics, 2008, Vol. 5, pp. 2886-2889.
H.B. Kekre, Tanuja Sarode, Prachi Natu, “Digital Image Compression using Hybrid Transform with Kekre Transform and Other Orthogonal Transforms”, Journal of Computer Engineering, Jan. 2014, Vol. 16, Issue 1, Ver. III, PP 38-46.
H. B. Kekre, Tanuja Sarode, Sudeep Thepade, Sonal Shroff, “Instigation of Orthogonal Wavelet Transforms using Walsh, Cosine, Hartley, Kekre Transforms and their use in Image Compression”, International Journal of Computer Science and Information Security, 2011, Vol. 9, No. 6, pp. 125-133.
H.B. Kekre, Tanuja Sarode, Prachi Natu, “ Image Compression Using Column, Row and Full Wavelet Transforms Of Walsh, Cosine, Haar, Kekre, Slant and Sine and Their Comparison with Corresponding Orthogonal Transforms”. International Journal of Engineering Research and Development (IJERD), Mar.2013, Vol. 6. Issue 4, pp. 102-113.
H.B. Kekre, Tanuja Sarode, Prachi Natu, “Image Compression using Real Fourier Transform, It’s Wavelet Transform and Hybrid Wavelet with DCT”, International Journal of Advanced Computer Science and Applications (IJACSA), 2013, Vol. 4, No.5, pp. 41-47.
H.B. Kekre, Tanuja Sarode, Prachi Natu, “Color Image Compression using Hybrid Wavelet Transform with Haar as Base Transform”, International Journal of Scientific and Research Publications, June 2014, Volume 4, Issue 6, pp. 1-13.
H.B. Kekre, Tanuja Sarode, Prachi Natu, “Performance Comparison of Hybrid Haar Wavelet Transform with Various Local Transforms in Image Compression using Different Error Metrics”, International Journal of Image Processing (IJIP), July 2014, Vol.8, Issue 4, pp. 186-203.
