Optimized Vector Quantization for Bayer Color Filter Array

Authors: M. Lakshmi, J. Senthil Kumar

Abstract:

Digital cameras to reduce cost, use an image sensor to capture color images. Color Filter Array (CFA) in digital cameras permits only one of the three primary (red-green-blue) colors to be sensed in a pixel and interpolates the two missing components through a method named demosaicking. Captured data is interpolated into a full color image and compressed in applications. Color interpolation before compression leads to data redundancy. This paper proposes a new Vector Quantization (VQ) technique to construct a VQ codebook with Differential Evolution (DE) Algorithm. The new technique is compared to conventional Linde- Buzo-Gray (LBG) method.

Keywords: Color Filter Array (CFA), Biorthogonal Wavelet, Vector Quantization (VQ), Differential Evolution (DE).

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1109806

References:

[1] Lukac, R., & Plataniotis, K. N. (2005). Color filter arrays: Design and performance analysis. Consumer Electronics, IEEE Transactions on, 51(4), 1260-1267.
[2] B. K. Gunturk, J. Glotzbach, Y. Altunbasak, R. W. Schafer and R. M. Mersereau (2004) Demosaicking: Color filter array interpolation in single chip digital cameras, IEEE Signal Process. Mag., no. 9.
[3] Naveen, L., Shobanbabu, B., & Tech, M. (2013). Color Filter Array Interpolation for Edge Strength Filters. International Journal of Engineering Trends and Technology (IJETT)-Volume4 Issue7-July.
[4] Chatterjee, N., & Dhole, A. (2014). Analysis of Image Demosaicking Algorithms.Analysis, 2(5).
[5] Li, X., Gunturk, B., & Zhang, L. (2008, January). Image demosaicing: A systematic survey. In Electronic Imaging 2008 (pp. 68221J-68221J). International Society for Optics and Photonics.
[6] Koh, C. C., Mukherjee, J., & Mitra, S. K. (2003). New efficient methods of image compression in digital cameras with color filter array. Consumer Electronics, IEEE Transactions on, 49(4), 1448-1456.
[7] Chung, K. H., & Chan, Y. H. (2008). A lossless compression scheme for Bayer color filter array images. Image Processing, IEEE Transactions on, 17(2), 134-144.
[8] Madhumalini, M., & Jayasudha, S. Prediction Based Lossless Compression Scheme for Bayer Color Filter Array Images.
[9] Lee, D. (2011). High Dynamic Range Image Compression of Color Filter Array Data for the Digital Camera Pipeline (Doctoral dissertation, University of Toronto).
[10] S. S. Mungona, &. Vishal V. Rathi (2014) Image Compression through VHDL Simulation
[11] Begel, A., Khoo, Y. P., & Zimmermann, T. (2010, May). Codebook: discovering and exploiting relationships in software repositories. In Software Engineering, 2010 ACM/IEEE 32nd International Conference on (Vol. 1, pp. 125-134). IEEE.
[12] Lazebnik, S., & Raginsky, M. (2009). Supervised learning of quantizer codebooks by information loss minimization. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 31(7), 1294-1309.
[13] Binit Amin., & Patel Amrutbhai (2014) Vector Quantization based Lossy Image Compression using Wavelets – A Review
[14] Feng, H. M., & Horng, J. H. (2011, August). VQ-Based fuzzy compression systems designs through bacterial foraging particle swarm optimization algorithm. In Genetic and Evolutionary Computing (ICGEC), 2011 Fifth International Conference on (pp. 256-259). IEEE.
[15] Wang, C. (2012, October). Bayer patterned image compression based on wavelet transform and all phase interpolation. In Signal Processing (ICSP), 2012 IEEE 11th International Conference on (Vol. 1, pp. 708- 711). IEEE.
[16] Doutre, C., & Nasiopoulos, P. (2009, November). Modified H. 264 intra prediction for compression of video and images captured with a color filter array. In Image Processing (ICIP), 2009 16th IEEE International Conference on(pp. 3401-3404). IEEE.
[17] Shinoda, K., Murakami, Y., Yamaguchi, M., & Ortega, A. (2012, May). An efficient compression method for one-shot multispectral camera. In Picture Coding Symposium (PCS), 2012 (pp. 269-272). IEEE.
[18] Kim, S., & Cho, N. I. (2014). Lossless compression of color filter array images by hierarchical prediction and context modeling. IEEE transactions on circuits and systems for video technology, 24(6), 1040- 1046.
[19] Aghagolzadeh, M., Moghadam, A. A., Kumar, M., & Radha, H. (2011, September). Compressive demosaicing for periodic color filter arrays. In Image Processing (ICIP), 2011 18th IEEE International Conference on (pp. 1693-1696). IEEE.
[20] Li, M. M., Song, Z. J., Yang, A. P., Hou, Z. X., & Huang, Z. (2011, June). Lossy compression of Bayer image with SPIHT. In Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on (pp. 2244-2248). IEEE.
[21] Zheng, J., Zhang, Q., & Zhang, X. (2009, August). Lossy Compression of CFA Image Based on Multiwavelet Packet. In Information Assurance and Security, 2009. IAS'09. Fifth International Conference on (Vol. 2, pp. 223-226). IEEE.
[22] Xu, X., & Hei, Y. (2009, October). A shortcut to compressing Bayerpattern imagery losslessly. In Image and Signal Processing, 2009. CISP'09. 2nd International Congress on (pp. 1-4). IEEE.
[23] Cheng, Y., Zhang, X., & Wen, J. (2010, September). Coding of Mosaic Image Based on Wavelet Sub-band Substitute. In Pervasive Computing Signal Processing and Applications (PCSPA), 2010 First International Conference on (pp. 679-683). IEEE.
[24] Lee, S. H., & Cho, N. I. (2010, September). H. 264/AVC based color filter array compression with inter-channel prediction model. In Image Processing (ICIP), 2010 17th IEEE International Conference on (pp. 1237-1240). IEEE.
[25] Malvar, H. S., & Sullivan, G. J. (2012, April). Progressive-to-lossless compression of color-filter-array images using macropixel spectralspatial transformation. In Data Compression Conference (DCC), 2012 (pp. 3-12). IEEE.
[26] Lee, D., & Plataniotis, K. N. (2012, September). A novel high dynamic range image compression scheme of color filter array data for the digital camera pipeline. In Image Processing (ICIP), 2012 19th IEEE International Conference on (pp. 325-328). IEEE.
[27] Reddy, V. P., & Varadarajan, S. (2010). An Effective Wavelet-Based Watermarking Scheme Using Human Visual System for Protecting Copyrights of Digital Images. International Journal of Computer and Electrical Engineering, 2(1), 32-40.
[28] Jiang, B., Yang, A., Wang, C., & Hou, Z. (2013). Implementation of Biorthogonal Wavelet Transform Using Discrete Cosine Sequency Filter.
[29] Varma, T., Chitre, V., & Patil, D., (2012) The haar wavelet and the biorthogonal wavelet transforms of an image.
[30] Prasad, B. R., Kota, K. V., & Reddy, B. M. (2012). Biorthogonal Wavelet Transform Digital Image Watermarking. International Journal of Advanced Computer Research, 2(3).
[31] Omran, M. G., Engelbrecht, A. P., & Salman, A. (2005, September). Differential evolution methods for unsupervised image classification. In Evolutionary Computation, 2005. The 2005 IEEE Congress on (Vol. 2, pp. 966-973). IEEE.
[32] Huang, Z., & Chen, Y. (2013). An improved differential evolution algorithm based on adaptive parameter. Journal of Control Science and Engineering, 2013, 3.
[33] Qin, A. K., & Suganthan, P. N. (2005, September). Self-adaptive differential evolution algorithm for numerical optimization. In Evolutionary Computation, 2005. The 2005 IEEE Congress on (Vol. 2, pp. 1785-1791). IEEE.