1. Digital Video Solutions to Midterm Exam 2008 Edited by Hung-Ming Wang Confirmed by Prof. Jar-Ferr Yang LAB: 92923 R, TEL: ext. 621 E-mail: ming@video5.ee.ncku.edu.twming@video5.ee.ncku.edu.tw Page of MPL: http://mediawww.ee.ncku.edu.twhttp://mediawww.ee.ncku.edu.tw

2. 2.1 (a) binary bits : { a 3, a 2,a 1,a 0 } (b) 0.01.0 0.875 1.0 0.88125 0.875 1 1 0 0 0 0.88125<W<0.8953, 111001 (57/64) Shadow Pixel 11000 Context number 813720 P( 0 | context number) 0.8750.050.1250.950.995 0.88125 0.8961 1.0 0.88125 0.8954 0.8953 0.8961 0.8954

3.  Significance Coding (Normal Mode) [ zero coding ]  Use to code new significance.  9 contexts according to the significance of its neighbors.  Significance Coding (Run Mode) [run length coding]  Group 4 insignificant coefficients when they are very probable.  Reduce the average number of symbols needed to be coded.  One context for whether all four are insignificant. Four Types of Coding Primitives 2.2

4. Four Types of Coding Primitives  Magnitude Refinement Coding  3 contexts depending on the significance of its neighbors and whether it is the first time for refinement.  Sign Coding  Used to code the sign right after a coefficient is identified significant.  5 contexts based on the sign of four neighbors.

5. Significance Coding (Normal Mode) Current sample Formation of significance coding context 2.2

6. Coding Passes  3 coding passes for each bit-plane, p  Significance Propagation Pass  Sample location j belongs to this pass if it is insignificant, but has a significant neighborhood  Magnitude Refinement Pass  For any sample which was already significant in the previous bit-plane  Cleanup Pass  Including all samples for which information has not already been coded in bit-plane p 2.2

7. Primitive of Each Coding Pass  Significant Propagation Passes  ZC + SC  Magnitude Refinement Pass  MR  Cleanup Pass  RLC + ZC + SC RLC ( 連續 4 個 0 ，且鄰居都是 0) 2.2

8. zc sc zc sc zc sc zc Significance Propagation Pass (Pass 1) 2.2 : Coefficient which is already significant : Significance Propagation Pass (Pass 1) 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 1 0 0 ZC: Zero Coding SC: Sign Coding (a)

9. zc sc zc sc zc sc zc Significance Propagation Pass (Pass 1) 2.2 : Coefficient which is already significant : Significance Propagation Pass (Pass 1) 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 1 0 0 ZC: Zero Coding SC: Sign Coding (a)

10. Magnitude Refinement Pass (Pass 2) : Magnitude Refinement Pass (Pass 2) : Significance Propagation Pass (Pass 1) zc sc zc sc zc sc zc 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 1 0 0

11. Clean-up Pass (Pass 3) : Pass 1 : Pass 2 : Pass 3 (ZC) : Pass 3 (RLC) ZC: Zero Coding SC: Sign Coding RLC

12. 2.2 (b) a: Magnitude refinement coding  h [j] = 1,  v [j] = 2,  d [j] = 1,  sig [j]=7  mag [j] = 15 or 16 b: ZC, LL band  h [j] = 1,  v [j] = 0,  d [j] = 1,  sig [j]=6 c: SC  h[j] = 0,  v[j] = 0, k sign [j] =9 d: RLC context number = 17 zc sc zc sc zc sc zc sc zc sc zc sc zc 0 0 0 0 0 1 1 0 1 0(a) 0 0 0 0(b) 0 1 0 1(c) 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0(e) 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0(f) 1 0 0 0 0 0 0 1 0 0 zc R L C zc R L C 0(d)

13. e: ZC, LL band  h [j] = 0,  v [j] = 0,  d [j] = 0,  sig [j]=0 f: Magnitude refinement coding  h [j] = 1,  v [j] = 1,  d [j] = 1,  sig [j]=7  mag [j] = 15 or 16 (we don’t know  [j]) 2.2 (b)

14. 2.2 (b)  sig [j] LL and LH blocksHL blocksHH blocks h[j]h[j] v[j]v[j] d[j]d[j] h[j]h[j] v[j]v[j] d[j]d[j] d[j]d[j]  h [j]+  v [j] 82xxx2x≥3x 71≥1x 1x2 610 01 20 51000001≥2 402x20x11 301x10x10 200 00 0 100100101 000000000 Assignment of context labels for significant coding “x” means “don’t care.”

15. 2.2 (b) h[j]h[j] v[j]v[j]  sign  flip 11131 10121 1111 01101 0091 010 111 012 13 Assignment of context labels and flipping factor for sign coding  h [j],  v [j]: neighborhood sign status -1: one or both negative. 0: both insignificant or both significant but opposite sign. 1: one or both positive. Current sample

16. 2.2 (b)  [j]  sig [j]  mag 0014 0>015 1X16 Assignment of context labels and flipping factor for magnitude refinement coding  [j]: remains zero until after the first magnitude refinement bit has been coded. For subsequent refinement bits,  [j] = 1.  sig  [j]: context label for significant coding of sample j

17. 2.2 (b) The entropy coder uses 19 different contexts which maybe summarized as follows: –Contexts 0 through 8 of the ZC primitive, –Contexts 9 through 13 of the SC primitive, –Contexts 14 through 16 of the MR primitive, –Contexts 17 of the RLC primitive, –Contexts 18 for the UNIFORM primitive.

18. 2.3. n -4-3-20123456789 x[n]x[n] 6-35-42 5-366-35-4 y 0 [2n]2.215010-1.750102.1250 010 y 1 [2n+1]0-8.50-7.50 0-8.50-70-8.50-7.5 x0[n]x0[n]-1.75-0.37511.56252.125 x1[n]x1[n]3.75-3.6254-4.56253.875-3.125 x’[n] 6-35-42 5-366-35-4 -2 1 0 1 2 y 0 [2n] y 0 [2n+1]

19. 2.4. (a) (b) (c) (d) (e) (f) 水平掃描電壓波幅不足 In Fig. g, H bias ckt has problem 垂直掃描電壓波幅不足 In Fig. g, V bias ckt has problem Clock 不同步 In Fig. g, V bias ckt has problem Video Amplifier (AGC) 有問題 In Fig. h, the video amp (upper one) has problem with improper DC offset. Blanking level 不正常 In Fig. h, the video amp (upper one) has problem Color decoder 有問題 In Fig. h, the video amp (lower one) or 2~4.2M BPF has problem normal abnormal vertical Incorrect time

21. 2.5 Initialization: LIP: { (0,0)  40, (0,1)  18, (1,0)  -20, (1,1)  15 } LIS: { D(0,1), D(1,0), D(1,1) } LSP: {} Significant Pass: 10 000 000 Refinement Pass: LIP: { (0,0)  40, (0,1)  18, (1,0)  -20, (1,1)  15 } LIS: {D(0,1), D(1,0), D(1,1) } LSP: { (0,0)  40 } (a) (b) 40 18 -20 6-6 46 77 6-7 2-3 00 15 SPIHT 48

22. Significant Pass: 10 11 0 000 Refinement Pass: 0 LIP: { (0,1)  18, (1,0)  -20, (1,1)  15 } LIS: { (0,1)D, (1,0)D, (1,1)D } LSP: { (0,0)  40, (0,1)  18, (1,0)  -20} Significant Pass: 10 000 up to 20 bits Generated bitstream: 10000000101100000100 40 18 -20 6-6 46 77 6-7 2-3 00 15 40

23. (c) Bitstream: 10 000 000 101100000100 48 0 0 00 00 00 00 00 00 0 Bitstream: 10000000 10 11 0 0 000 100 40 24 -24 00 00 00 00 00 00 0 (1) (2) (3) 40 20 -20 00 00 00 00 00 00 12

24. EZW : –DWT SPIHT : –DWT, set partioning EBCOT : –DWT, block, bit-plane, RDO, resolution & SNR scalable 2.6

25. 2.7 p(A) = 0.50, p(B) = 0.25, p(C) = 0.10, p(D)=p(E) = p(F) = 0.05 (a) Huffman code: A 0 (1) B 10 (01) C 110 (001) D 1110 (0001) E 11110 (00001) F 11111 (00000) A 0.5 B 0.25 C 0.10 D 0.05 E 0.05 F 0.05 1 0 1 1 1 0 0 0 1 0 (b) RVLC code : A 0 B 101 C 11011 D 1110111 E 111101111 F 111111111

26. (c) Original Huffman code: 0, 10, 110, 1110, 11110, 11111 0 1 11 101 100 1000 1001 10001 10000 10 1 0 1010 1011 10101 10100 10111 10110 100001 100000 Optimal symmetrical RVLC A 0 B 11 C 101 D 1001 E 10001 F 100001 optimal symmetrical RVLC : 從後面長

27. 0 1 11 101 001 0001 1001 10001 00001 01 0 1 Prefix conflict Optimal asymmetrical RVLC A 0 B 11 C 101 D 1001 E 10001 F 100001 100001 000001 (d) Original Huffman code: 0, 10, 110, 1110, 11110, 11111 optimal asymmetrical RVLC : 從前面長

28. 1.(a) Color Substracting Mixing vs. Color Additive Mixing ex: ink ex: light dyes 1.(b) QMF vs. Subband Coding

29. 1.(c) Bringhtness versus Hue 1.(d) Error Resilience versus Reversible VLC

30. 1.(e) Simultaneous Effect versus Weber’s Law 同一顏色會受到相鄰顏色 ( 背景色 ) 的影響 1.(f) ROI versus MaxShift