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DCT with Quad tree and Huffman Coding for Color Images

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Sandhya Kadam, Vijay Rathod

Sandhya Kadam and Vijay Rathod. DCT with Quad tree and Huffman Coding for Color Images. International Journal of Computer Applications 173(9):33-37, September 2017. BibTeX

	author = {Sandhya Kadam and Vijay Rathod},
	title = {DCT with Quad tree and Huffman Coding for Color Images},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2017},
	volume = {173},
	number = {9},
	month = {Sep},
	year = {2017},
	issn = {0975-8887},
	pages = {33-37},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017915431},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Many methods are available for compression of an image file. Images are usually in the form of matrices and an uncompressed image uses a huge number of bytes for storage. Its applications in various fields are quality control, remote sensing, imaging science etc. The image compression methods which are popular on the transform based coding methods like Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and fractals. However, these methods have drawbacks like low compression ratio and high encoding time. The proposed hybrid technique combines DCT and fractal quad tree decomposition with Huffman encoding of fixed threshold value for color images. The results for the proposed method are displayed and compared for performance parameters as compression ratio, encoding time, decoding time and PSNR.


  1. M. Barnsley, “Fractals Everywhere”, New York, Academic 1988.
  2. A. E. Jaquin, “Image Coding based on a fractal theory of iterated contractive image transformation”, IEEE Transaction on Image Processing, 1992.
  3. X. Y. Wang, D. D. Zhang, “Discrete Wavelet Transform based simple range classification strategies for fractal image coding”, Non Linear Dy. 75, 3, pp.439-448, 2014.
  4. Rene J. Richard P, Christian H, “ Low complexity Scalable DCT Image Compression, IEEE, 2000.
  5. Dr. Loay E George, Nevart A. Minas, “ Speeding up Fractal Image Compression using DCT Descriptors”, Journal of Information and Computing Science, vol.6, No. 4, 2011, pp 287-294.
  6. Dr. Eman A, Dr. Loay E. George, “Study of Fractal Color Image Compression using YUV Component”, IEEE 36th International Conference on Computer Software and Applications, 2012.
  7. Ching Hung Yuen, Oi Yan Lui, Kwok Wo Kong, “Hybrid fractal image coding with quad tree based progressive structure”, J. Vis. Communication and Image Representation, 24(2013), 1328-1341.
  8. Shiwangi, Sanjay Kumar, Analysis of Image Compression Algorithm Using DCT, DFT and DWT Transforms. International Journal of Advanced Research in Computer Science and Software Engineering Vol. 6, Issue 7, July 2016.
  9. Prabhakar. Telagarapu, V.Jagan Naveen,“Image Compression Using DCT and Wavelet Transformations “International Journal of Signal Processing, Image Processing and Pattern Recognition ,Vol. 4, No. 3, September2011.
  10. A. A. Shaikh, P. P. Gadekar, Huffman Coding Technique for Image Compression.”International Journal of Advanced Computer Technology” Vol.4, Issue 4 , April-2015.
  11. R.Praisline Jasmi, B.Perumal, M.Pallikonda Rajasekaran, ‘Comparison Of Image Compression Techniques Using Huffman Coding, Dwt And Fractal Algorithm’ International Conference on Computer Communication and Informatics,Coimbatore, India, Jan. 08 – 10, 2015.
  12. Padmavati.S, Dr. Vaibhar MesharamDCT Combined With Fractal Quad tree Decomposition and Huffman Coding for Image Compression’ International Conference on Condition Assessment Techniques in Electrical Systems.
  13. Rachit Patel, Virendra K, Vaibhav T, Vishal A,’A fast and Improved Image Compression technique using Huffman coding’, IEEE, International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET),Pages: 2283 – 2286, 2016.
  14. Surekha R Gondkar, Girish V Attimarad, B. Chandrasekhar,’Compression of 2D image using 3D DCT’
  15. Kulkarni S, Naik A, Nagori N, A comparison of real valued transforms for image compression, Int. Jour. Eng. Sci 4(1), 17, 2008.
  16. Annadurai S, Sundaresan M, Wavelet based color image compression, Proceedings of the International Conference on Advances in Computing, Communication and Control, USA, pp. 391-396, 2009.


DCT, Fractal Quad tree, Huffman coding, Fractal Image Compression, Hybrid methodology