COMP 9519: Tutorial 1

Transcription

1 COMP 9519: Tutorial 1 1. An RGB image is converted to YUV 4:2:2 format. The YUV 4:2:2 version of the image is of lower quality than the RGB version of the image. Is this statement TRUE or FALSE? Give reasons for your answer. 2. Shown below are two 8x8 image blocks. Calculate the entropy associated with each block Block A Block B

2 3. Based on 2x2 macroblocks (MB), the X motion estimation algorithm (X- MEN) searches for the best matching motion vector in the following locations: {0,0}, {-2,-2}, {+2,-2}, {-2, +2}, {+2,+2}. These locations are relative to the current MB and corresponds to the center, top-left, top-right, bottom-left and bottom-right areas. Assume a search range of {-2,+2}, with the current MB at the current frame (frame[n]) as: And the reference frame (frame[n-1]) is: Where the shaded MB is the relative position of the current MB in frame[n] on the reference frame (also called the co-located MB). Answer the following questions: i) Calculate the sum of absolute differences at each search location of X- MEN. ii) What will be the best motion vector given by X-MEN? Justify your answer.

3 4. The video encoding process blocks are shown below: Answer the following questions: i) Which block(s) will information loss occur? ii) iii) iv) Which block(s) contain the decoded version of the previous frame (Frame[N-1])? Which block(s) contain the motion compensated version of the current frame (Frame[N])? Assume the current frame is inter-coded (i.e. coded using motion estimation), what will the coded video consist of?

4 5. An 8x8 image block is given below. (i) Transform this block using the 2D DCT, (ii) perform quantization using a step size of 8 for all transformed coefficients, (iii) perform zig-zag scanning of the quantized coefficients to obtain (run, level) pairs, (iv) perform inverse quantization, (v) perform 2D IDCT, (vi) calculate MSE of the final inverse quantized, inverse transformed block The 1D DCT matrix that can be used for this question is given below Note that 2D DCT can be performed by : C X C T

5 Where C is the DCT matrix given above and the superscript T denotes a transpose; and X denotes the image block being transformed. To calculate the 2D Inverse DCT (2D IDCT) remember that C C T = I Where I denotes the identity matrix; you can deduce the 2D IDCT from this relationship. Quantization can be performed by a simple integer division of the transformed coefficients by the quantization step size (i.e. integer division by 8 in this question). Alternatively you can use the mid-tread quantizer given in Lecture 2 ( with a step size of 8). 6. Using the VLC scheme detailed in the lecture slides, can you try to code some of the (run, length) pairs obtained in the previous question? 7. Assume you have a video sequence coded in the following pattern IBBPBBPBBPBBIBBPBBPBBPBBI (i) (ii) (iii) (iv) If the second I frame is corrupted with error (i.e. the I frame in the middle of the above sequence), how many other frames can be degraded due to error propagation? You can assume, for example, that a portion of the data for the second I frame is missing (i.e due to lost packets in a streaming application). Similarly what would be the effect of error propagation if the first B frame is corrupted with error? How can such error propagation be limited for an MPEG-4 coded bit stream? How can scalable coding help with error resilience in a video streaming application? Assume you have spatial scalable coding with two layers (base layer and enhancement layer) and that video is being streamed live (ie IPTV).