DocumentCode :
2871646
Title :
A Hybrid Image Compression Algorithm based on Human visual system
Author :
Jiang, Chunlei ; Yin, Shuxin
Author_Institution :
Electr. & Inf. Eng. Coll., Northeast Pet. Univ., Daqing, China
Volume :
9
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
In this paper, we present an efficient hybrid image compression method. According to Human eye sensitivity, It is not sensitive to gray-scale error, but the human eye is particularly sensitive to the image edge features, through we research strengths and weaknesses of the fractal image coding and SPIHT(set partitioning in hierarchical trees) algorithm, proposed a hybrid algorithm based on SPIHT and Fractal image compression algorithm, it makes full use of landscape features and human visual characteristics, the image is decompounded into low frequency sub-band and high frequency sub-band, then the low frequency sub-band is uses fractal coding, this could make the low-frequency information loss less who is sensitivity to human visual signal and the high frequency sub-band is uses SPIHT coding, so encoding time greatly reduced. Experimental results show that the Hybrid Image Compression Algorithm not only raises the coding efficiency and reconstructed image quality but also reduces the image encoding time.
Keywords :
data compression; edge detection; grey systems; image coding; set theory; SPIHT; fractal image coding; fractal image compression algorithm; gray scale error; high frequency subband; human eye sensitivity; human visual system; hybrid algorithm; hybrid image compression algorithm; image edge features; image encoding time; image quality; low frequency information; set partitioning in hierarchical trees; Algorithm design and analysis; Fractals; Humans; Image coding; Image edge detection; Partitioning algorithms; Time frequency analysis; DCT; DWT; HVS; SPIHT; fractal coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5623059
Filename :
5623059
Link To Document :
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