1. 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

2. Outline Introduction Edge-directed prediction The proposed method
Experimental results
Conclusions

3. Introduction Lossy image compression Lossless image coding
Natural image
Vector quantization, JPEG…
Lossless image coding
Medical image
Run length, Huffman coding, arithmetic coding…

4. 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”

5. 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

6. 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)

7. 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

8. 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

9. Experimental results

10. Experimental results (cont.)

11. Experiment results (cont.)

12. Conclusions Propose a simple yet effective edge detector
A good tradeoff between computational complexity and the prediction results has been obtained