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  1. 1. Research Topic Error Concealment Techniques in H.264/AVC for Wireless Video Transmission Vineeth Shetty Kolkeri EE Graduate,UTA
  2. 2. <ul><li>Purpose of H.264 / MPEG-4 part 10 </li></ul><ul><ul><li>Higher coding efficiency than previous standards, MPEG-1,2,4 part 2, H.261, H.263 </li></ul></ul><ul><ul><li>2. Simple syntax specifications </li></ul></ul><ul><ul><li>3. Seamless integration of video coding into all current protocols </li></ul></ul><ul><ul><li>4. More error robustness </li></ul></ul><ul><ul><li>5. Various applications like video broadcasting, video streaming, video conferencing, D-Cinema, HDTV </li></ul></ul><ul><ul><li>6. Network friendliness </li></ul></ul><ul><ul><li>7. Balance between coding efficiency, implementation complexity and cost - based on state-of the-art in VLSI design technology </li></ul></ul>
  3. 3. Better image quality at the same compressed bitrate, or a lower compressed bitrate for the same image quality.
  4. 4. Basic Coding Structure for H.264 [1]
  5. 5. Error Control <ul><li>Goal of Error Control : Overcome the effect of errors, during the transmission of the video frames in the wireless medium, e.g. packet loss on a packet network on a wireless network. </li></ul><ul><li>2 . Method used for Error Control : Error Concealment </li></ul>
  6. 6. <ul><li>Error Concealment </li></ul><ul><li>Problem: Transmission errors may result in lost information </li></ul><ul><li>2. Goal: Estimate the lost information in order to conceal the fact that an error has occurred </li></ul><ul><li>3. Error concealment is performed at the decoder </li></ul><ul><li>4. Observation: Video exhibits a significant amount of correlation along the spatial and temporal dimensions </li></ul><ul><li>5. Basic approach: Perform some form of spatial/temporal Concealment to estimate the lost information from correctly received data </li></ul>
  7. 7. <ul><li>Error Concealment (cont.) </li></ul><ul><li>Consider the case where a single macroblock (16x16 block of pixels) is lost </li></ul><ul><li>Three examples of error concealment: </li></ul><ul><li>1.Spatial Concealment: </li></ul><ul><ul><li>Estimate missing pixels by smoothly extrapolating surrounding pixels </li></ul></ul><ul><ul><li>Correctly recovering missing pixels is extremely difficult, however even correctly estimating the DC (average) value is very helpful </li></ul></ul><ul><li>2.Temporal Concealment: </li></ul><ul><ul><li>Copy the pixels at the same spatial location in the previous frame </li></ul></ul><ul><ul><li>Effective when there is no motion, potential problems when there is motion </li></ul></ul><ul><li>3.Motion-compensated temporal Concealment: </li></ul><ul><ul><li>Estimate missing block as motion-compensated block from prior frame </li></ul></ul><ul><ul><li>Can use coded motion vector, neighboring motion vector, or compute new motion vector </li></ul></ul>
  8. 8. <ul><li>Motion Vector Extrapolation (MVE) </li></ul><ul><ul><li>Compensate the missed MB by extrapolating each MV that is stored in previously decoded frame. </li></ul></ul><ul><ul><li>2. 8x8 sub-block based process. </li></ul></ul><ul><ul><li>3. Large overlapped MV is selected for the sub-block. </li></ul></ul><ul><ul><ul><li>If there is no overlap, then use Zero MV. </li></ul></ul></ul>
  9. 9. 4. Error Concealment – MB missing <ul><li>Zero MV </li></ul><ul><ul><li>Replaces missed MV as (0,0) </li></ul></ul><ul><ul><li>Copy a macro-block from previously reconstructed reference slice at the exact </li></ul></ul><ul><ul><li>same position </li></ul></ul>Zero MV concealment in dispersed FMO slices
  10. 10. <ul><li>Error Concealment – Frame missing </li></ul><ul><li>1. Temporal Replacement </li></ul><ul><li>Copy a MB/Frame from previously reconstructed reference slice at the </li></ul><ul><li>exact same position </li></ul><ul><li>2. Motion Vector Copy </li></ul><ul><li>Exploits MVs of a few past frames </li></ul><ul><ul><li>Estimate the MV of each pixel in last successful frame </li></ul></ul><ul><ul><li>Project last frame onto an estimate of missing frame </li></ul></ul>
  11. 11. Frames# 5, 6 and 7 of the Original Sequence Frame# 5 of the decoded frame, Successfully decoded lost Frame # 6. Frame# 6 was reconstructed by Frame copy. Frame #7 is degraded. Temporal Replacement - Frame Copy
  12. 12. &quot;Inter&quot; temporal prediction – block based motion estimation and compensation 1. Multiple reference pictures 2. Reference P pictures 3. Arbitrary referencing order 4. Variable block sizes for motion compensation Seven block sizes: 16x16, 16x8, 8x16, 8x8, 8x4, 4x8 & 4x4 5. 1/4-sample luma interpolation (1/4 or 1/8th-sample chroma interpolation) 6. Weighted prediction 7. Frame or Field based motion estimation for interlaced scanned video
  13. 13. Frames# 5, 6 and 7 of the Original Sequence Frame# 5 of the decoded frame, Successfully decoded lost Frame # 6. Frame# 6 was reconstructed by Motion Copy algorithm. Frame #7 is degraded. <ul><ul><li>Motion Vector Copy </li></ul></ul>
  14. 14. Different Error Concealment Techniques Ref: I.C.Todoli “Performance of Error Concealment Methods for Wireless Video”, Diploma Thesis, Vienna University of Technology, 2007 [1] Original Error Weighted Average Decode I Frame without residuals Decode without residuals Copy-paste Boundary matching Block matching
  15. 15. <ul><li>1. Tested the Frame copy and Motion Estimation in the decoder. </li></ul><ul><li>2. Implementing the Error Concealment algorithms in the decoder of JM 13.2. </li></ul><ul><li>Compare results of the recovered frames by error concealment technique from </li></ul><ul><li>MSE : It calculates the “difference” between two images. It can be applied to digital video by averaging the results for each frame . </li></ul><ul><li>PSNR : The most commonly used objective quality metric is the Peak Signal to Noise Ratio (PSNR). For a video sequence of frames. </li></ul><ul><li>SSIM: This approach emphasizes that the Human Visual System (HVS) is highly adapted to extract structural information from visual scenes. Therefore, a measurement of structural similarity (or difference) should provide a good approximation to perceptual image quality. </li></ul>Implementation and Video Quality Analysis of the Received Sequences
  16. 16. <ul><li>Future Work </li></ul><ul><li>Implementing the various Error Concealment algorithm using JM 13.2 </li></ul><ul><li>Software. </li></ul><ul><li>2. Evaluating the quality of recovered frames. </li></ul>
  17. 17. References <ul><li>T. Stockhammer, M. M. Hannuksela and T. Wiegand, “H.264/AVC in </li></ul><ul><li>Wireless Environments”, IEEE Trans. Circuits and Systems for Video </li></ul><ul><li>Technology, Vol . 13, pp. 657- 673, July 2003. </li></ul><ul><li>2. Soon-kak Kwon, A. Tamhankar and K.R. Rao, ” Overview of H.264 / MPEG-4 Part 10 ” , J. Visual Communication and Image Representation , vol. 17, pp.186-216, April 2006. </li></ul><ul><li>3. S. Wenger, “H.264/AVC over IP ” IEEE Trans. Circuits and Systems for Video Technology , vol. 13, pp. 645-656, July 2003. </li></ul><ul><li>4. M. Wada, “Selective Recovery of Video Packet Loss using Error Concealment,” IEEE Journal on Selected Areas in Communication , vol. 7, pp. 807-814, June 1989. </li></ul><ul><li>5. I.C.Todoli “Performance of Error Concealment Methods for Wireless Video”, Diploma Thesis, Vienna University of Technology, 2007 . </li></ul><ul><li>6. Video Trace research group at ASU, “Yuv video sequences,” . </li></ul><ul><li>7. A.B. Watson, &quot;Toward a perceptual video quality metric&quot;, Human Vision, Visual Processing, and Digital Display VIII, 3299, pp 139-147, 1998. </li></ul><ul><li>8. F. Xiao, “Dct-based video quality evaluation,” Final Project for EE392J Stanford Univ. 2000. </li></ul><ul><li>9. Z. Wang, “The SSIM index for image quality assessment,” . </li></ul>