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Volume 6, Issue 4
Speeding Up Fractal Image Compression Using DCT Descriptors

Loay E. George and Nevart A. Minas

J. Info. Comput. Sci. , 6 (2011), pp. 287-294.

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  • Abstract
The main problem in the Fractal image compression (FIC) method is the long encoding time. In order to speed up the encoding stage, an improved PIFS scheme is introduced in this paper; In the introduced PIFS scheme the input color image is, converted from RGB color space to YUV color space, and then the chromatic bands are down sampled by 2. The zero-mean range and domain blocks are classified using a block descriptor which is determined using a pair of low frequency DCT coefficients due to the energy packing properties of DCT. The DCT descriptors are also used to address the isometric state of each range and domain blocks. The coefficients of the optimal affine approximation are quantized, and then coded using differential pulse code modulation (DPCM) and shift coding. The conducted tests results on Lena's standard image indicated that the encoding time is reduced to (1 sec) while keeping the image quality above the acceptable level and no significant reduction in the compression ratio was occurred.
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@Article{JICS-6-287, author = {Loay E. George and Nevart A. Minas}, title = {Speeding Up Fractal Image Compression Using DCT Descriptors}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {6}, number = {4}, pages = {287--294}, abstract = {The main problem in the Fractal image compression (FIC) method is the long encoding time. In order to speed up the encoding stage, an improved PIFS scheme is introduced in this paper; In the introduced PIFS scheme the input color image is, converted from RGB color space to YUV color space, and then the chromatic bands are down sampled by 2. The zero-mean range and domain blocks are classified using a block descriptor which is determined using a pair of low frequency DCT coefficients due to the energy packing properties of DCT. The DCT descriptors are also used to address the isometric state of each range and domain blocks. The coefficients of the optimal affine approximation are quantized, and then coded using differential pulse code modulation (DPCM) and shift coding. The conducted tests results on Lena's standard image indicated that the encoding time is reduced to (1 sec) while keeping the image quality above the acceptable level and no significant reduction in the compression ratio was occurred. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22670.html} }
TY - JOUR T1 - Speeding Up Fractal Image Compression Using DCT Descriptors AU - Loay E. George and Nevart A. Minas JO - Journal of Information and Computing Science VL - 4 SP - 287 EP - 294 PY - 2024 DA - 2024/01 SN - 6 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22670.html KW - AB - The main problem in the Fractal image compression (FIC) method is the long encoding time. In order to speed up the encoding stage, an improved PIFS scheme is introduced in this paper; In the introduced PIFS scheme the input color image is, converted from RGB color space to YUV color space, and then the chromatic bands are down sampled by 2. The zero-mean range and domain blocks are classified using a block descriptor which is determined using a pair of low frequency DCT coefficients due to the energy packing properties of DCT. The DCT descriptors are also used to address the isometric state of each range and domain blocks. The coefficients of the optimal affine approximation are quantized, and then coded using differential pulse code modulation (DPCM) and shift coding. The conducted tests results on Lena's standard image indicated that the encoding time is reduced to (1 sec) while keeping the image quality above the acceptable level and no significant reduction in the compression ratio was occurred.
Loay E. George and Nevart A. Minas. (2024). Speeding Up Fractal Image Compression Using DCT Descriptors. Journal of Information and Computing Science. 6 (4). 287-294. doi:
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