1. ECE 533 Project - Removing Blocking artifacts and Ringing artifacts in the Compressed Image Member : Park, Byung Kwan (single member)

2. Ⅰ. Introduction… • Two Artifacts due to Transform-Based compression… - 1. Blocking Artifacts : direct result of block processing - 2. Ringing Artifacts : appearing along the edges like sharp oscillation or ghost shadows

3. How to solve these two artifacts… - Using the theory of projections onto convex sets (POCS) method - Line processing along the horizontal, vertical, and two diagonal directions - Setting new smoothness constraint sets

4. Ⅱ. Approach… • Constraint Sets (For blocking Artifacts) - Due to quantized block discrete-cosine transform (BDCT) - To suppress blocking artifacts along the vertical boundaries - Considering blocking artifacts severer along the edge

5. Constraint Sets ( For ringing artifacts ) - Ringing artifacts occur around the edges, not the edge pixels - Leaving the edge and processing neighboring pixels - Arising the necessity of line processing to detect edges - Four directional (horizontal, vertical and two diagonal ) smoothness constraint sets based on each directional line processing

6. For horizontal direction Where lv(i,j) = 1 , if these exits an edge between the pixels (i,j) and (i,j+1) 0 , otherwise - Making Vh(f) small enforce smoothness along the horizontal direction in an image - New constraint set - Other directions are also similar to horizontal direction

7. Ⅲ. Methods… • Divide-And-Conquer method for smoothness constraint sets - Projections to four directional sets have numerical difficulty - Divide the image into blocks to calculate projections - Special attentions to window function in the smoothness sets also gives us the opportunity to remove the blocking artifacts

8. For Projection onto Horizontal Constraint sets 1) For each i = 1,2,…,N and for each j = 8b with b = 0,1,…,Nk Whereif lv(I,j+k)=1 Otherwise 2) For the rest of the pixels - Vertical case is similar to this case

9. For Projection onto Diagonal Constraint sets 1) For(i,j)∈Dd with d=1,2,5,6,9,10... Whereif lp(i,j)=1 Otherwise 2) The rest of the image pixels unchanged

10. Ⅳ. Implementation… ( Parameters ) • Line-Processing - Using statistical threshold • Visibility Weights - For removing blocking artifacts and ringing artifacts at the same time • Smoothness Bounds

11. Original Image Compress JPEG Image Ⅴ. Results…

12. Line-Processing

13. Compressed Image and Recovered Image

14. Ⅵ. Discussion… • One parameter ramda in projection Eq. • - It is the solution of non-linear Eq. • - I just input various values • Four directional Projections • - Just two directional projections implemented • Ringing artifacts • - The still image doesn’t show many ringing artifacts

15. Ⅶ. References… • - Galatsanos, Removal of compression artifacts using projections onto convex sets and line process modeling IEEE Trans. Image Processing, vol. 6, pp. 1345-1357, 1997 • - S. Yang, Y. H. Hu, D. L. Tull, and T. Q. Nguyen, Maximum likelihood parameter estimation for image ringing artifact removal IEEE Trans. Circuits and Systems for Video Technology, vol. 11, 2001.