2. 1 Pixel Interpolation By: Mieng Phu Supervisor: Peter Tischer

3. 2 Outline What is pixel interpolation? Applications Project Aims Lossless Image Processing Image and Video Processing Methodology Work so far achieved Summary

4. 3 What is pixel interpolation? Pixel (or pels) is used to denote the elements of a digital image. An image is a 2D array of pixels with different intensity. Interpolation is to alter, invent or introduce by insertion a new matter. Hence, the fundamental concept of Pixel Interpolation to invent or predict missing pixels.

5. 4 BeforeAfter

6. 5 Applications Image and Video Processing Digital Camera-Color interpolation Scheme (CCD image sensor) Printers Internet - Web Browsers Flat Panel Display (FPD) like LCD, Plasma.. Medical science imaging. Videophone

7. 6 Project Aims The idea of this project is to look at how missing pixel values are estimated in lossless image processing (L.I.C). Then to investigate how these techniques can be applied in other areas of image and video processing, where pixel interpolation is needed.

8. 7 Lossless Image Compression (L.I.C) The fundamental concept of L.I.C. reduce the amount of data required to represent an image, so that we can retain its originality. Also known as Lossless Predictive Coding  Symbol Encoder Compressed Image Predictor Input Image

9. 8 So how are missing pixel values estimated in L.I.C ? Images are normally coded in raster order. Based on the past input pixels, the predictor generates the anticipated value dependent on the predictor. Various local, global, and adaptive predictors. known values How would we predict this ?

10. 9 Lossless Image Compression Techniques Some lossless image compression prediction techniques are: –Local approximation Polynomial exaction –exact for flat region –exact for linear gradient –Multiple Predictors Switching Blending –Least squares approaches

11. 10 Interlacing Video and Deinterlacing A complete frame Odd line Even line Lower or even field Upper or odd field

12. 11 E.g. AB frame - odd lines from picture A and even lines from picture B with a time shift of 1/24 seconds - Object moving between fields. Position in field A Position in field B

13. 12 Image and Video Processing In image and video processing, missing pixels must be estimated to avoid problems. Situations where pixel interpolation is needed: –Deinterlacing within a single field –Deinterlacing using current and past field –Deinterlacing using the past, current and future field (motion compensation estimation) –SDTV to HDTV (Magnification)

14. 13 Deinterlacing(1) Deinterlacing within a single frame - use the odd lines to predict the even lines. xxx xxx ??? x - Known values ? - Unknown values Current field Time t i

15. 14 Deinterlacing(2) Deinterlacing of two frames - use the even lines of the previous frame and odd lines of the current frame, also motion vectors. ??? ??? xxx xxx xxx ??? Current fieldPrevious field t i - 1 titi

16. 15 Deinterlacing(3) Motion Compensation and Estimation- use previous, current and future frame with motion vectors to create a highly quality and resolution video. ??? ??? xxx xxx xxx ??? ??? ??? xxx t i - 1 titi t i +1 Previous fieldCurrent fieldFuture field

17. 16 Converting from SDTV to HDTV - could be done by deinterlacing the rows and then deinterlacing the columns. x?x x?x ??? HDTV xx xx SDTV Magnification

18. 17 Methodology Start Points –Study still images and single frame –Try using known pixels from different positions. –Switching predictors from L.I.C –Blending predictors from L.I.C

19. 18 Work so far achieved ? Implementation of Tao Chen Edge Line Averaging (ELA) algorithm for deinterlacing within a single frame. Implementation of the existing algorithms for deinterlacing- generic ELA, Adaptive ELA, Line Doubling. Comparison between algorithms. Remarks: Tao Chen algorithm can be improved.

20. 19 Summary There are many application on image and video processing in which missing pixel values must be estimated. This project investigates how existing techniques from lossless image compression can be applied in other areas of image and video processing, where pixel interpolation needed.

21. 20 Any Questions..