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Published byВасилий Старовойтов Modified over 5 years ago
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Adaptive Lossless Image Coding Using Least Squares Optimization With Edge-Look-Ahead
Source: IEEE Transactions on Circuits and Systems, Vol. 52, No. 11, Nov. 2005, pp Authors: Kau, Lih-Jen and Lin, Yuan-Pei Speaker: Chou, Yung-Chen Date: Mar. 2, 2006
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Outline Introduction Edge-directed prediction The proposed method
Experimental results Conclusions
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Introduction Lossy image compression Lossless image coding
Natural image Vector quantization, JPEG… Lossless image coding Medical image Run length, Huffman coding, arithmetic coding…
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Introduction (cont.) N. Kuroki et al., (1992): “Lossless image compression by two-dimensional linear prediction with variable coefficients” X. Li and M. T. Orchard, (2001): “Edge-directed prediction for lossless compression of natural images”
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Introduction (cont.) Least square (LS) prediction Pa=y
xn(11) xn(8) xn(6) xn(9) xn(12) xn(7) xn(3) xn(2) xn(4) xn(10) xn(5) xn(1) xn Pa=y Minimize the square errors
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Introduction (cont.) M=2T(T+1) 143 145 139 144 138 152 142 149 136 153
135 151 150 20 26 25 141 140 30 22 35 28 27 29 32 M=2T(T+1)
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Edge-directed prediction (Li and Orchard, 2001)
143 145 139 144 138 152 142 149 136 153 135 151 150 20 26 25 141 140 30 22 35 28 27 29 32 If > th then adapt LS Else using previous coefficients a
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The proposed method Edge detector Causal pixel Current pixel (xn)
100 110 240 230 115 236 50 56 60 45 70 Current pixel (xn) Kl={xn(1)=110, xn(2)=110, xn(3)=100} Kh={xn(4)=240} Condition: 100 10
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Experimental results
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Experimental results (cont.)
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Experiment results (cont.)
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Conclusions Propose a simple yet effective edge detector
A good tradeoff between computational complexity and the prediction results has been obtained
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