A Hybrid Edge-Enhanced A Hybrid Edge-Enhanced Motion Adaptive DeinterlacerMotion Adaptive Deinterlacer

By Marc Ramirez

• Canon GL1 “Frame Mode” ~ 320 Vertical Lines• Deinterlace from 60i into a 30p sequence

• High Quality, Noise Reduction, Edge & Detail Preservation, Moderate Complexity

• MC Recursive, VT Median, EDDI, BOB• Best Approach Depends on Material

Field A Field B Field C

Frame 1

Problem Statement & MotivationProblem Statement & Motivation

Initially Proposed MethodInitially Proposed Method

Simonetti

de Haan

Actual MethodActual Method

Current DV Capture Cards Import 60i Sequences as Field-Merged 30p

1) Store First Three Fields (A,B,C) from Captured Frames1 & 2

2) Look at the SAD of Fields A & C, If <= Thresh1 -> Keep Original Frame *

Ex. Mounted Camera Recording a Stationary Object; White Background

3) Detect Edges

*Could Potentially Cause Problems

Two Types of Edge Detection

• EDDI Horizontal Emphasis

• Canny Method in Matlab Edge Function

- Smoothing By Gaussian Convolution

- 2D Derivative

- Ridge Tracking of Gradient Magnitude

4) Interpolate Along Found Edges

- Step Through Known Lines Only

- Pick a Test Block of Correct Length

- Use SAD to Determine Best Match

- If <= Thresh2 -> Interpolate

- Use Nearest Neighbor if Between Pixels

Known

Known

Known

5) Fill In Static Areas

IF

AND

Fill In With Previous or Average of Pixel P&N

3ThreshLUMLUM NP

32

)(

2

)(Thresh

LUMLUMLUMLUM EBNP

44/ ThreshLcLaKcKaJcJaIcIa

6) Detect If Slow Pixel Motion

7) Use Median Filter on Small Window B = SUM/|DIFF| for ( 4 Combinations)

Med{E[A,F] E[B,E] E[C,D] E[G,H] lowB}

8) Spatially Interpolate Remaining High-Motion Pixels

• 4 Tap Vertical Filter for Better Frequency Response

• Might Also Include a Horizontal Component

Conclusion/Future ChangesConclusion/Future Changes

• Overall the Implementation is Less Computationally Expensive than MC with Pretty Nice Results

• The Algorithm Tries to Use the Proper Method Based on Simple Motion Detection

• Many Threshold Parameters -> Difficult to Set the Correct Thresholds for All Cases

• Could Later Implement EDDI Correctly on the Final Image

• Future Method Could Incorporate Motion Estimation

• Implement a Plug-in For Virtual Dub or AVISynth

ReferencesReferences

[1] R. Simonetti, S. Carrato, G. Ramponi and A.Polo Filisan, 'Deinterlacing of HDTV Images for Multimedia Applications', in Signal Processing of HDTV, IV, E. Dubois and L. Chiariglione, Eds., Elsevier Science Publishers, 1993, pp. 765-772.

[2] G. de Haan and E.B. Bellers, ‘Deinterlacing -- An overview', Proceedings of the IEEE, Vol. 86, No. 9, Sep. 1998, pp. 1839- 1857.

[3] G. de Haan and R. Lodder, `De-interlacing of video data using motion vectors and edge Information', Digest of the ICCE'02, Jun. 2002, pp. 70-71.

[4] G. de Haan, `Video processing for multimedia systems', ISBN: 90-9014015-8, Eindhoven Sep.  2000.

[5] Y. Wang, J. Ostermann, and Y.Q. Zhang, ‘Video Processing and Communications’ Prentice Hall, 2002, ISBN 0-13-017547-1.