Authors:
Hafeez Ullah Jan,Dr. Gul Muhammad,Atif Jan,Muhammad Aamir Aman,DOI NO:
https://doi.org/10.26782/jmcms.2020.03.00018Keywords:
Artificial Neural Network (ANN),Hidden Neurons,MATLAB,Image Compression,Reconstruction,Abstract
Excessive use of electronic devices and image sharing applications in the modern world produce gigantic number of images. The huge image data demands to be handled properly to efficiently utilize the storage space and transmission bandwidth resources. Image compression techniques limit the storage size of the image for this purpose. With the passage of time compression techniques have enhancedto attain more compression and produce decompressed image of high quality. This study which is part of post graduate project suggests the use of neural network to reconstruct the gray scale images which are compressed by withdrawing the pixels from the image. MATLAB is used as programming tool to carry out the simulations. The results obtained are promising.Refference:
I. Asuni, N., & Giachetti, A. (2013). Testimages: A large data archive for display and algorithm testing. Journal of Graphics Tools, 17(4), 113-125.
II. Drew, P. J., & Monson, J. R. (2000). Artificial neural networks. Surgery, 127(1), 3-11.
III. Gardner, M. W., & Dorling, S. R. (1998). Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences. Atmospheric environment, 32(14-15), 2627-2636.
IV. Gonzales, R. C., & Woods, R. E. (2002). Digital image processing (Vol. 2). New Jersey: Prentice hall.
V. Jain, A. K. (1981). Image data compression: A review. Proceedings of the IEEE, 69(3), 349-389.
VI. Marsalli, M. (2006). Mcculloch-pitts neurons. In The 2008 Annual Meeting of the consortium on cognitive science instruction (ccsi) (pp. 172-179).
VII. Nelson, M., & Gailly, J. L. (1996). The data compression book (pp. 457-458). New York: M & t Books.
VIII. Warner, B., & Misra, M. (1996). Understanding neural networks as statistical tools. The american statistician, 50(4), 284-293.
IX. Yang, M., & Bourbakis, N. (2005, August). An overview of lossless digital image compression techniques. In 48th Midwest Symposium on Circuits and Systems, 2005. (pp. 1099-1102). IEEE.