Video and Vision Processing Suite Intel® FPGA IP User Guide

ID 683329
Date 4/03/2023

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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 Intel® FPGA IP 8. 3D LUT Intel® FPGA IP 9. AXI-Stream Broadcaster Intel® FPGA IP 10. Chroma Key Intel® FPGA IP 11. Chroma Resampler Intel® FPGA IP 12. Clipper Intel® FPGA IP 13. Clocked Video Input Intel® FPGA IP 14. Clocked Video to Full-Raster Converter Intel® FPGA IP 15. Clocked Video Output Intel® FPGA IP 16. Color Space Converter Intel® FPGA IP 17. Deinterlacer Intel® FPGA IP 18. FIR Filter Intel® FPGA IP 19. Frame Cleaner Intel® FPGA IP 20. Full-Raster to Clocked Video Converter Intel® FPGA IP 21. Full-Raster to Streaming Converter Intel® FPGA IP 22. Genlock Controller Intel® FPGA IP 23. Generic Crosspoint Intel® FPGA IP 24. Genlock Signal Router Intel® FPGA IP 25. Guard Bands Intel® FPGA IP 26. Interlacer Intel® FPGA IP 27. Mixer Intel® FPGA IP 28. Pixels in Parallel Converter Intel® FPGA IP 29. Scaler Intel® FPGA IP 30. Stream Cleaner Intel® FPGA IP 31. Switch Intel® FPGA IP 32. Tone Mapping Operator Intel® FPGA IP 33. Test Pattern Generator Intel® FPGA IP 34. Video Frame Buffer Intel® FPGA IP 35. Video Streaming FIFO Intel® FPGA IP 36. Video Timing Generator Intel® FPGA IP 37. Warp Intel® FPGA IP 38. Design Security 39. Document Revision History for Video and Vision Processing Suite User Guide

29.3.2. Coefficient Quantization

The scaler IP implements the filters when you select Polyphase algorithm using fixed-point logic, so you must supply the filter coefficients in a fixed-point format. You define the format for the coefficients with parameters that select whether they are signed or unsigned, the number of integer bits, and the number of fraction bits.
  • Signed or unsigned: if you want to represent negative coefficients, turn on Use signed vertical coefficients. If all coefficients are positive values, reduce logic and turn off Use signed vertical coefficients.
  • Integer bits: the number of integer bits defines the maximum value that can be represented.
  • Fraction bits: the number of fraction bits defines the precision with which the IP can convert floating-point coefficients into the fixed-point format.

The overall bit width of each coefficient is the sum of the integer and fraction bits, plus one extra bit for signed coefficients. When using Lanczos coefficients, Intel recommends the following settings:

  • Turn on Use signed vertical coefficients as the Lanczos function for any number of lobes greater than 1 requires negative values, so the coefficients must be signed.
  • Use 1 integer bit as the maximum value required for any Lanczos coefficient is 1.0
  • Use between 6 and 8 fraction bits.

Typically, the filter coefficients produce noninteger floating-point values. To convert each floating-point coefficient into its closest quantized representation in the selected fixed-point format:

  • Multiply each coefficient by 2 frac , where frac is the number of fraction bits you select
  • Apply float to integer conversion to each coefficient

However, small errors in the coefficient values introduced by the quantization process can accumulate so that the coefficients in each phase no longer sum to their intended value. Generally, the coefficients in any phase should sum to exactly 1.0. Any value greater than 1.0 increases the overall brightness of the resulting image. Any value less than 1.0 reduces the brightness. The coefficients can sum to more or less than 1.0 if you want a brighter or darker image. You should still ensure your coefficients sum to your original, intended value post quantization. To restore the coefficients to values that sum to the intended value:

Figure 63. Restore Coefficient Values
float quantization_error = 0.0;
for (int j = 0; j < taps; j++) {
   quantization_error += original_float_coeff[j] - ((float)quant_coeff[j]);
   if (quantization_error < -0.5) {
      quantization_error += 1.0;
   } else {
      if (quantization_error > -0.5) {
         quantization_error -= 1.0;