Removing Redundancy from the Image Using Buffering Mechanism

Authors

  • Suman Kumari  Department of Computer Science and Engineering, Guru Nanak Dev University RC, Gurdaspur, India
  • Sona Khanna  Department of Computer Science and Engineering, Guru Nanak Dev University RC, Gurdaspur, India
  • Taqdir  Department of Computer Science and Engineering, Guru Nanak Dev University RC, Gurdaspur, India

Keywords:

Redundancy, image processing, image, buffer, pixel, buffering.

Abstract

The redundancy is a problem which remains when we talk about the concept of image processing. Redundancy is present when image contain some repeated value of pixel. There are number of techniques which are used to resolve the problem of redundancy. In the proposed system buffer method is used in order to resolve the problem of redundancy. The problem of redundancy is considerably reduced when the concept of buffering is used. The proposed method we will use buffer in order to store the pixel values which can be compared against the other pixel values which present in buffer and to reject them if they are repeated. So, by proposed method the redundancy from the image is eliminated.

References

  1. L. Yu and H. Liu, "Efficient Feature Selection via Analysis of Relevance and Redundancy," vol. 5, pp. 1205–1224, 2004.
  2. P. Ulbrich, M. Hoffmann, R. Kapitza, D. Lohmann, and W. Schröder-preikschat, "Eliminating Single Points of Failure in Software-Based Redundancy," pp. 49–60, 2012.
  3. J. S. A. N. Pedro and S. Siersdorfer, "Content Redundancy in YouTube and its Application to Video Tagging," 2007.
  4. S. Kalyuga, P. Chandler, and J. Sweller, "Human Factors : The Journal of the Human Factors and Ergonomics Society," 2004.
  5. "Digital Image Processing for Image Enhancement and Information Extraction."
  6. P. B. Tambe, P. D. Kulhare, M. D. Nirmal, and P. G. Prajapati, "Image Processing ( IP ) Through Erosion and Dilation Methods," vol. 3, no. 7, pp. 285–289, 2013.
  7. A. Kaur and J. Kaur, "Comparision of Dct and Dwt of Image Compression Techniques," vol. 1, no. 4, pp. 49–52, 2012.
  8. I. Compression and C. F. Size, "Fundamentals of Image Compression Image Compression ( cont .)."
  9. V. Bastani, M. S. Helfroush, and K. Kasiri, "Image compression based on spatial redundancy removal and image inpainting," vol. 11, no. 2, pp. 92–100, 2010.
  10. S. A. Khayam, "( DCT ):," 2003.
  11. I. M. Agus and D. Suarjaya, "A New Algorithm for Data Compression Optimization," vol. 3, no. 8, pp. 14–17, 2012.
  12. S. Abdul, K. Jilani, and S. A. Sattar, "JPEG Image Compression using FPGA with Artificial Neural Networks," vol. 2, no. 3, 2010.
  13. E. The, "Chapter 2," pp. 32–54.
  14. R. E. Mayer and R. Moreno, "Nine Ways to Reduce Cognitive Load in Multimedia Learning," vol. 38, no. 1, pp. 43–52, 2003.
  15. R. a.M, K. W.M, E. M. a, and W. Ahmed, "Jpeg Image Compression Using Discrete Cosine Transform - A Survey," Int. J. Comput. Sci. Eng. Surv., vol. 5, no. 2, pp. 39–47, 2014.
  16. D. Kumar and Sonal, "A Study Of Various Image Compression," Conf. Challenges Oppor. Inf. Technol., pp. 1–5, 2007.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2017-12-31

Issue

Volume 2, Issue 2, March-April-2016

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Suman Kumari, Sona Khanna, Taqdir, " Removing Redundancy from the Image Using Buffering Mechanism, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 2, pp.775-777, March-April-2016.