Video and Vision Processing Suite IP User Guide

ID 683329
Date 3/30/2025
Public

Visible to Intel only — GUID: ijw1661937234333

Ixiasoft

Document Table of Contents
1. About the Video and Vision Processing Suite 2. Getting Started with the Video and Vision Processing IPs 3. Video and Vision Processing IPs Functional Description 4. Video and Vision Processing IP Interfaces 5. Video and Vision Processing IP Registers 6. Video and Vision Processing IPs Software Programming Model 7. Protocol Converter IP 8. 1D LUT IP 9. 3D LUT IP 10. Adaptive Noise Reduction IP 11. Advanced Test Pattern Generator IP 12. AXI-Stream Broadcaster IP 13. Bits per Color Sample Adapter IP 14. Black Level Correction IP 15. Black Level Statistics IP 16. Chroma Key IP 17. Chroma Resampler IP 18. Clipper IP 19. Clocked Video Input IP 20. Clocked Video to Full-Raster Converter IP 21. Clocked Video Output IP 22. Color Plane Manager IP 23. Color Space Converter IP 24. Defective Pixel Correction IP 25. Deinterlacer IP 26. Demosaic IP 27. FIR Filter IP 28. Frame Cleaner IP 29. Full-Raster to Clocked Video Converter IP 30. Full-Raster to Streaming Converter IP 31. Genlock Controller IP 32. Generic Crosspoint IP 33. Genlock Signal Router IP 34. Guard Bands IP 35. Histogram Statistics IP 36. Interlacer IP 37. Mixer IP 38. Pixels in Parallel Converter IP 39. Scaler IP 40. Stream Cleaner IP 41. Switch IP 42. Text Box IP 43. Tone Mapping Operator IP 44. Test Pattern Generator IP 45. Unsharp Mask IP 46. Video and Vision Monitor Intel FPGA IP 47. Video Frame Buffer IP 48. Video Frame Reader Intel FPGA IP 49. Video Frame Writer Intel FPGA IP 50. Video Streaming FIFO IP 51. Video Timing Generator IP 52. Vignette Correction IP 53. Warp IP 54. White Balance Correction IP 55. White Balance Statistics IP 56. Design Security 57. Document Revision History for Video and Vision Processing Suite User Guide

39.3.1. Coefficient Selection

If you select polyphase scaling for the Scaler IP, the coefficients that the scaling filters use are read from a memory. You must define the contents of this memory. Either specify fixed horizontal and vertical coefficient sets in the Horizontal coefficient function and Vertical coefficient function parameters or turn on Update coefficients at runtime. If you turn on Update coefficients at runtime, you can write whatever values you want to the coefficient memory. If you already have well defined coefficient sets that you use, the flexibility in the scaler to select the desired number of filter taps and phases should allow you to continue with these. If you are new to scaling, read the following guidance on coefficient selection.

Generally, the set of coefficients that the IP writes to filter phase 0 yield a low-pass filter, with most weight in generating the output pixel value given to the pixel value in tap . The function is centered at tap . The coefficients the IP writes to the other phases are then just phase-shifted versions of this function (hence the name phase for each coefficient address), with the function centered at a point that is shifted by 1/ num_of_pixels of a pixel with every subsequent phase.

Figure 103. 2-lobe Lanczos function at 3 different phases This figure shows an example of how a function is progressively phase-shifted to create the coefficients for each scaling filter phase. The figure shows a 4 tap filter, with the taps shown on the x-axis

The Lanczos function is a common function that defines scaling coefficients. The Lanczos function is a base sinc function, with the primary lobe of a sinc function used as a window function to preserve a given number of lobes of the base sinc. The number of lobes is generally appended to Lanczos when referring to a specific variant of the function, so a Lanczos function where two lobes are preserved is referred to as Lanczos2. In the case where N lobes are preserved, the LanczosN function is defined as:

Equation 9. Coefficient Selection Equation

When using LanczosN coefficients, Intel recommends configuring the scaler filters with the following numbers of taps for the upscale and downscale cases:

  • Upscale: 2 × N
  • Downscale:

The number of lobes in the Lanczos function affects the frequency response of the filter and, as a result, the quality of the image produced. Generally, Lanczos functions with lower numbers of lobes give a softer frequency response and a resulting image with more blur on the edges, but with less risk of ringing artifacts in the areas immediately around the edges. Conversely, Lanczos functions with higher numbers of lobes give sharper edges but introduce more ringing artifacts. Lanczos2 is a good compromise between minimizing blur and minimizing ringing, but you can experiment with Lanczos3 or Lanczos4 to make your own judgment. The higher the number of lobes, the more filter taps (and therefore FPGA device resources) the design requires to implement the filter correctly. You should experiment with Lanczos1 coefficients for large downscales.