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De Interlacing Techniques

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This presentation discusses the various techniques used for video de-interlacing.

This presentation discusses the various techniques used for video de-interlacing.

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  • 1. De-Interlacing Techniques
    Ramesh Prasad
  • 2. Introduction
    De-interlacing is the process of converting interlaced video, such as common analog television signals or 1080i format HDTV signals, into a non-interlaced form.
    Interlaced video frame consists of two sub-fields taken in sequence, each sequentially scanned at odd and even lines of the image sensor; analog television employed this technique because it allowed for less transmission bandwidth and matched the properties of CRT screens.
    However, most current displays are inherently progressive, so the two fields need to be combined to a single frame, which leads to various visual defects which the de-interlacing process should try to avoid.
  • 3. Introduction
    Progressive Frame
    Odd Field
    Even Field
  • 4. Introduction
    Interlacing is a form of “Spatio-temporal” sub sampling
    De-interlacing is the reverse operation, aiming at removal of sub-sampling artifacts
    For stationary pictures (no camera or object motion or intensity changes) the de-interlacing is trivial as alternating even and odd fields completely describe the captured scene
    However, for pictures with camera/object motion and intensity changes (which always is the case with real life scenario); de-interlacing becomes non-trivial and entails processing, as it requires interpolation of picture data that was never transmitted or even captured.
    A good de-interlacing algorithm should try to avoid interlacing artifacts as much as possible and not sacrifice image quality in the process.
  • 5. Introduction
  • 6. Techniques for De-Interlacing
    Intra field de-interlacing
    Inter field de-interlacing
    Spatio-Temporal Interpolation
    Motion adaptive de-interlacing
    Motion compensated de-interlacing
  • 7. Intra field de-interlacing - Overview
    Based on Spatial filtering
    Exploits the correlation between vertically neighboring samples in a field when interpolating intermediate pixels
    They have all pass temporal frequency response which guarantees the absence of motion artifacts
    Low computational cost
    Loss of vertical details and artifacts when the object exists in only one parity field
  • 8. Intra field de-interlacing – Scan line duplication (Bob)
    The missing line is generated by duplicating the line directly above it
    Cons-
    Jagged effect will occur in the oblique line
    flicker
    Blur
  • 9. Intra field de-interlacing – Scan line duplication (Bob)
    Jagged Effect
    Flicker
    Flicker
  • 10. Intra field de-interlacing – Scan line interpolation
    The missing line is generated by taking the average of the lines vertically above and below it
    Less blur, flicker and jagging than scan line duplication method
  • 11. Intra field de-interlacing – Edge Line Average (ELA)
    Interpolation is done in the direction of edge
    Three pixels in the previous scan line and the next scan line are referenced to determine the obvious edge in the image
    This method can eliminate the blurring effect of the bilinear interpolation and gives sharp/straight edges.
  • 12. Intra field de-interlacing – Edge Line Average (ELA)
  • 13. Inter field de-interlacing - Overview
    Based on Temporal filtering
    Exploits the correlation between temporally neighboring samples between fields when interpolating intermediate pixels
    They have all pass spatial frequency response which guarantees the absence of artifacts for stationary pictures
    Low computational cost but require additional field memory
    Artifacts in areas where motion occurs
  • 14. Inter field de-interlacing – Field Insertion (Weave)
    • The two fields are “woven” into one frame
    • 15. It is best solution in case of still images as all vertical frequencies are preserved
    • 16. If there is motion between the even and odd fields being woven; artifact called serration or mouse teeth occurs because the moving objects are not shown at the same position for even and odd lines of the single output frame
    Odd Field
    Even Field
  • 17. Inter field de-interlacing – Field Insertion (Weave)
    Difference between Bob and Weave
    Bob
    Weave
  • 18. Inter field de-interlacing – Field Insertion (Weave)
    Mouse Teeth Artifact
  • 19. Inter field de-interlacing – Temporal Averaging
    Types -
    Mean –
    Display a half-picture that is created as the average of the two original half-pictures
    The Mean algorithm simply pairs the original lines, and averages each pair into one output line. Line 1 of output is the mean of lines 1 and 2 in input, line 2 of output is the mean of lines 3 and 4 in input, and so on.
    Blend –
    Each line of the picture is created as the average of a line from the odd and a line from the even half-pictures.
    This ignores the fact that they are supposed to be displayed at different times
    The first line of output is copied from the first line of input. For any other output line N, the line is the mean of input lines N and N-1. That is, the second line of output is the mean of lines 1 and 2 in input, the third line is the mean of lines 2 and 3, ... and finally, the last line of output is the mean of the last two lines in input. The sliding averaging procedure preserves the original vertical resolution.
    Pros – Mouse Teeth artifact is avoided
    Cons – Artifact called ghosting is introduced
  • 20. Inter field de-interlacing – Temporal Averaging
    Ghosting Artifact
  • 21. Spatio-Temporal Interpolation - Overview
    Based on Spatio-Temporal filtering
    Exploits the correlation between both spatially and temporally neighboring samples when interpolating intermediate pixels
    The filter is usually designed such that the contribution from the neighboring fields is limited to the higher vertical frequencies
    Hence, motion artifacts are absent for objects without vertical details that move horizontally
    The vertical detail from the previous field is being combined with the temporally shifted current field, so some motion artifacts may occur.
  • 22. Spatio-Temporal Interpolation
  • 23. Motion adaptive de-interlacing - Overview
    It combines the advantages of both intra-field and inter-field interlacing
    It detects the motion first, and then adopts intra field de-interlacing in motion areas and inter-field de-interlacing in static areas
    High resolution and flicker free picture can be realized in motion and static area
    It relies on accurate motion detection; erroneous detection cause artifacts
  • 24. Motion adaptive de-interlacing
  • 25. Motion adaptive de-interlacing
    The motion detection block detects the motion between the two fields
    The output of the motion detection block controls the selector switch for the intra or inter interpolated values
    For moving image parts, intra interpolated values are passed and for static image parts inter interpolated values are passed
    Finally an interleaving switch interleaves the current field and the interpolated sample to form the progressive frame
    The intra and inter interpolation mechanism could be any of the techniques described earlier
  • 26. Motion adaptive de-interlacing
    Instead of a switch, a fade mechanism could be used which combines the intra and inter interpolated samples
    • Fst is the result of interpolation for static image parts
    • 27. Fmot is the result of interpolation for moving image parts
    • 28. Motion detector determines the mix factor “alpha” with “alpha” = 0 for very high motion and “alpha” = 1 in absence of motion
  • Motion adaptive de-interlacing – Motion Detection
    Same-parity-field detection
    For interlaced video, the vertical position of even field and odd field is slightly different
    Same-parity-field detection detects the motion area by the even-field to even-field or odd-field to odd-field difference
  • 29. Motion adaptive de-interlacing – Motion Detection
  • 30. Motion adaptive de-interlacing – Motion Detection
    4-Field motion detection
    To improve the accuracy of motion detection, 4 fields rather than 2 fields are used
    The fields are labeled backward, current, forward and forward-forward
    The differences are computed for fields of same parity; backward-forward and current-forward-forward
  • 31. Motion adaptive de-interlacing – Motion Detection
  • 32. Motion adaptive de-interlacing – Motion Detection
  • 33. Motion adaptive de-interlacing – Implicit Adaptation (Median Filtering)
    Median Filtering adapts implicitly to motion
    The simplest version is a 3-tap spatio-temporal filter which uses the immediate vertical up, down and temporal neighbor in the previous field
    The underlying assumption is that in case of stationarity, the temporal neighbor is likely to have a value between that of the vertical neighbors of the current field
    In case of motion, intra-field interpolation is likely to result, since the correlation between the samples in the current field is likely to be highest
    Hence Median filtering automatically realizes the intra/inter switch
    Pros: Superior properties at vertical edges and low hardware cost
    Cons: Distortion of vertical details and introduction of alias
  • 34. Motion adaptive de-interlacing – Implicit Adaptation (Median Filtering)
  • 35. Motion compensated de-interlacing - Overview
    It’s the most advanced technique for interpolation
    Motion compensated method try to interpolate in the direction with highest correlation; with motion vector available, this is the interpolation along the motion trajectory
    It allows the moving sequences to be converted virtually into stationary ones and use methods which work well on stationary sequences like line insertion etc.
    Motion compensated methods needs to be combined with scene change detection, otherwise it will attempt to find motion between two completely different scenes
    Usually a combination of Edge directed spatial interpolation and motion compensated temporal interpolation is used in practice
    It outperforms other techniques in terms of quality of the de-interlaced frame
    It’s the most complex and processing intensive technique as it involves motion estimation
  • 36. Motion compensated de-interlacing
  • 37. Motion compensated de-interlacing
    Motion estimation is performed on the fields of same parity (backward and forward fields) as they have the same sampling grid
    Half pel/quarter pel accuracy can be used for motion estimation
    As the backward and forward fields are of different parity than the current field, the blocks need to be shifted to the sampling grid of the current field
    To obtain the position of the block in the current interpolated field from the previous field, the motion vectors are halved and the blocks of backward, current and forward field moved simultaneously to the sampling grid of the current interpolated field
  • 38. Motion compensated de-interlacing
    Block shifting to match the sampling grid
    Pixel value in the current interpolated field
  • 39. Motion compensated de-interlacing
    To handle scene change detection, the pixel values obtained by motion compensated interpolation are compared with the spatial edge directed interpolated pixel values
    If the difference is beyond the threshold value, its assumed that interpolation based on motion estimation is incorrect
    In such case, directional interpolation is used instead of motion compensated interpolation
    The motion compensated/edge directed interpolated pixels are finally combined to get the progressive frame
  • 40. References
    Altera White Paper - High-Definition Video Deinterlacing Using FPGAs
    Deinterlacing - An Overview
    GERARD DE HAAN, ERWIN B. BELLERS
    Deinterlacing using directional interpolation and motion compensation
    Ohjae Kwon, KwanghoonSohn, Chulhee Lee
    Motion Adaptive Interpolation with Horizontal Motion Detection for Deinterlacing
    Shyh-Feng Lin, Yu-Ling Chang, and Liang-Gee Chen
  • 41. Thank You

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