Presentation 1996/3/8
Subband Texture Image Coding According to the Statistical Property
Masae YOKOTA, Yasunari YOKOTA, Akira IWATA,
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Abstract(in English) Segmentation image coding which decomposes an original image into some objective segments is an essential technique for next decade image coding. On segmentation coding, how objective texture images after segmentation are compressed is one of the important subjects. Recently, Komatsu etc. designed subband filter which optimize coding gain for image of AR process, and shows that coding gain for normal image improve about 0.5[dB]. But there are large differences among autocorrelation function of each texture image, and it was proposed that texture image coding by subband filter is designed according to each auto-correlation function. As a result, Coding Brodatz's texture image using 1-layer 5 taps filter, improved coding gain to 0.87[dB] and 1.5[dB] compared with AR model filter with 5 taps and orthogonal wavelet filter with 6 taps respectively.
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Keyword(in English) subband coding / texture / coding gain / image compression / orthogonal wavelet transform
Paper # CAS95-124,DSP95-179,CS95-202
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Committee CAS
Conference Date 1996/3/8(1days)
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Registration To Circuits and Systems (CAS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Subband Texture Image Coding According to the Statistical Property
Sub Title (in English)
Keyword(1) subband coding
Keyword(2) texture
Keyword(3) coding gain
Keyword(4) image compression
Keyword(5) orthogonal wavelet transform
1st Author's Name Masae YOKOTA
1st Author's Affiliation Nagoya Bunri College()
2nd Author's Name Yasunari YOKOTA
2nd Author's Affiliation Nagoya Institute of Technology
3rd Author's Name Akira IWATA
3rd Author's Affiliation Nagoya Institute of Technology
Date 1996/3/8
Paper # CAS95-124,DSP95-179,CS95-202
Volume (vol) vol.95
Number (no) 556
Page pp.pp.-
#Pages 6
Date of Issue