Two Improved Color Images Compression Systems

Authors

  • A. A. El-Harby Damietta University, Faculty of Science, Math. Department, New Damietta, 34517, Egypt

Keywords:

Quadtree, Color Image Compression, Image Processing

Abstract

In this paper, two image compression systems are designed based on quadtree (QT). They can compress the colour images for the three components separately. The proposed systems divides colour images into their three components. Then, the first two components (R and G) are divided into blocks using QT method. While the division of the B component has the same blocks coordinates of the G component. The first system has three minimum values (MVs) and three difference values (DVs) for each block. In the second system for R component, one MV and one DV are identified for every block. While for the other two components, two MVs and one average difference (AD) are determined for any block. As a result, it is found that the division according to the G component is the best giving good compressed images with high compression ratios and visual quality. In addition to, the second system is the best one having the highest performance. This system has the highest accuracy rates in the compression ratios, peak-to-peak signal to noise ratio (PSNR) values, number of blocks and low computational time comparing with the first system.

References

Shikang Kong, Lijuan Sun, Chong Han, Jian Guo, "An Image Compression Scheme in Wireless Multimedia Sensor Networks Based on NMF", Information, vol. 8, no. 26, pp.1-14, 2017.

Mansour Nejati, Shadrokh Samavi, Nader Karimi, Sayed Mohammad Reza Soroushmehr, Kayvan Najarian, "Boosted Dictionary Learning for Image Compression", IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 25, no. 10, pp. 4900-4915, 2016.

Miguel Hernández-Cabronero, Ian Blanes, Armando J. Pinho, Michael W. Marcellin, Joan Serra-Sagristà , "Progressive Lossy-to-Lossless Compression of DNA Microarray Images", IEEE SIGNAL PROCESSING LETTERS, vol. 23, no. 5, pp. 698-702, 2016.

Petr Pata, Jaromir Schindler, "Astronomical context coder for image compression", Experimental Astronomy, vol. 39, no. 3, pp 495-512, 2015.

CuipingShi, JunpingZhang, Ye Zhang, "Content-based onboard compression for remote sensing images", Neurocomputing, vol. 191, pp. 330-340, 2016.

Ke-KunHuang, HuiLiu, Chuan-XianRen, Yu-FengYu, Zhao-RongLai, "Remote sensing image compression based on binary tree andoptimized truncation", Digital Signal Processing, vol. 64, pp. 96-106, 2017.

Charles Z. Liu, Manolya Kavakli, "Extensions of principle component analysis with applications on vision based computing", Multimedia Tools and Applications, vol. 75, no. 17, pp 10113-10151, 2014.

Jing Tang, Yun’an Hu, Tao Lin, Yongxing Xie, "Electronic Equipment Real-time Monitoring System Design based on Huffman compression principle", 2nd International Conference on Signal Processing Systems (ICSPS), pp. 763-765, 2010.

Mohammad-Shahram Moin, "Face recognition in JPEG compressed domain: a novel coefï¬cient selection approach", Signal, Image and Video Processing, vol. 9 , no. 3, pp 651-663, 2015.

Rong Zhang, Rang-Ding Wang, "In-camera JPEG compression detection for doubly compressed images", Multimedia Tools and Applications, vol. 74, no. 15, pp 5557-5575, 2015.

SanuThomas, ThomaskuttyMathew, "Lossless address data compression using quadtree clustering of the sensors in a grid based WSN", Ad Hoc Networks, vol. 56, pp. 84-95, 2017.

Xingsong Hou a,n, MinHan a, ChenGong b, XuemingQian, "SAR complex image data compression based on quadtree and zerotree Coding in Discrete Wavelet Transform Domain: A Comparative Study", Neurocomputing, vol. 148, pp. 561-568, 2015.

WeiMA, XunLIU, "Improving the efficiency of DAMAS for sound source localization via wavelet compression computational grid", Journal of Sound and Vibration, vol. 395, pp. 341-353, 2017.

K. Srinivasan, Justin Dauwels, M. Ramasubba Reddy, "Multichannel EEG Compression: Wavelet-Based Image and Volumetric Coding Approach", IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, vol. 17, no. 1, pp. 113-120, 2013.

Mamata Panigrahy, Indrajit Chakrabarti, A. S. Dhar, "Low-Delay Parallel Architecture for Fractal Image Compression", Circuits, Systems, and Signal Processing, vol. 35, no. 3, pp 897-917, 2016.

VijayshriChaurasia, VaishaliChaurasia, "Statistical feature extraction based technique for fast fractal image compression", Journal of Visual Communication and Image Representation, vol. 41, pp. 87-95, 2016.

Mayur Prakash, Deepak Arora, "An Approach Towards Lossless Compression Through Artificial Neural Network Techinique", Int. Journal of Engineering Research and Applications, vol. 5, no. 7 (Part-1), pp.93-99, 2015.

Abir JaafarHussain, DhiyaAl-Jumeily, NaeemRadi, PauloLisboa, "Hybrid Neural Network Predictive-Wavelet Image Compression System", Neurocomputing, vol. 151, pp.975-984, 2015.

Hui Li Tan, Chi Chung Ko, Susanto Rahardja, "Fast Coding Quad-Tree Decisions Using Prediction Residuals Statistics for High Efficiency Video Coding (HEVC)", IEEE TRANSACTIONS ON BROADCASTING, vol. 62, no. 1, pp. 128-133, 2016.

Hamid Reza Tohidypour, Mahsa T. Pourazad, Panos Nasiopoulos, "Probabilistic Approach for Predicting the Size of Coding Units in the Quad-Tree Structure of the Quality and Spatial Scalable HEVC", IEEE TRANSACTIONS ON MULTIMEDIA, vol. 18, no. 2, pp. 182-195, 2016.

El-Harby A.A., Behery G.M., "Qualitative Image Compression Algorithm Relying on Quadtree", International Journal on Graphics, Vision and Image processing (GVIP), vol. 8, no. 3, pp. 41-50, 2008.

Tamer Rabie, Ibrahim Kamel, "Toward optimal embedding capacity for transform domain steganography: a quad-tree adaptive-region approach", Multimedia Tools and Applications, vol. 76, no. 6, pp 8627-8650, 2017.

Yu-Chen Hu, Ji-Han Jiang, "Low-complexity progressive image transmission scheme based on quadtree segmentation", Real-Time Imaging, vol. 11, no. 1, pp.59-70, 2005.

El-Harby A. A., Behery G. M., "Novel Color Image Compression Algorithm Based on Quad tree", Global Journal of Computer Science and Technology (F), Volume 12, no. 13, Version 1.0, PP. 13-22, 2012.

Hui Liu, Ke-Kun Huang, Chuan-Xian Ren, Yu-Feng Yu, Zhao-Rong Lai, "Quadtree coding with adaptive scanning order for space-borne image compression", Signal Processing: Image Communication, vol. 55, pp. 1-9, 2017.

Downloads

Published

2017-10-26

How to Cite

Two Improved Color Images Compression Systems. (2017). Asian Journal of Applied Sciences, 5(5). https://ajouronline.com/index.php/AJAS/article/view/4979

Similar Articles

11-20 of 60

You may also start an advanced similarity search for this article.