Rescale

Overview

The Rescale algorithm is used to scale the input image by means of resampling its content to make it conform to the output image dimensions.

No pre-filtering is applied, it's expected that the input content doesn't have frequencies higher than the Nyquist limit to avoid aliasing artifacts when downsampling.

Several interpolation methods are available, allowing trade-offs between quality and performance.

Input	Factor	Output
	\begin{align*} f_x &= 2/3 \\[5pt] f_y &= 3/2 \end{align*}

Implementation

For every output pixel, calculate the corresponding input pixel using the formula:

\[ \mathit{out}[x,y] = P(f_x x, f_y y) \]

where P depends on the interpolation method used.

Sampling operation considers that whole coordinates fall on pixel center.

Usage

1. Initialization phase
   1. Include the header that defines the rescale function.

      #include <vpi/algo/Rescale.h>

   2. Define the input image object.

          VPIImage input = /*...*/;

   3. Create an output image with the new required size and same format as input.

          uint32_t w, h;
          vpiImageGetSize(input, &w, &h);
       
          VPIImageFormat type;
          vpiImageGetType(input, &type);
       
          VPIImage output;
          vpiImageCreate(w * 2 / 3.0f, h * 3 / 2.0f, type, 0, &output);

   4. Create the stream where the algorithm will be submitted for execution.

          VPIStream stream;
          vpiStreamCreate(0, &stream);

2. Processing phase
   1. Submit the algorithm to the stream along with all parameters. It'll be executed by the CUDA algorithm.

          vpiSubmitRescale(stream, VPI_BACKEND_CUDA, input, output, VPI_INTERP_LINEAR_FAST, VPI_BOUNDARY_COND_ZERO);

   2. Optionally, wait until the processing is done.

          vpiStreamSync(stream);

3. Cleanup phase
   1. Free resources held by the stream and the input and output images.

          vpiStreamDestroy(stream);
          vpiImageDestroy(input);
          vpiImageDestroy(output);

Consult the Rescale for a complete example.

For more details, consult the Rescale API reference.

Limitations and Constraints

Constraints for specific backends supersede the ones specified for all backends.

All Backends

• Input and output images must have the same dimensions and type.
• The following interpolation methods are supported:
  • VPI_INTERP_NEAREST
  • VPI_INTERP_LINEAR
  • VPI_INTERP_LINEAR_PRECISE
  • VPI_INTERP_CATMULL_ROM
  • VPI_INTERP_CATMULL_ROM_PRECISE
• The following image formats are accepted:
  • VPI_IMAGE_FORMAT_U8
  • VPI_IMAGE_FORMAT_S8
  • VPI_IMAGE_FORMAT_U16
  • VPI_IMAGE_FORMAT_S16
  • VPI_IMAGE_FORMAT_RGB8
  • VPI_IMAGE_FORMAT_BGR8
  • VPI_IMAGE_FORMAT_RGBA8
  • VPI_IMAGE_FORMAT_BGRA8
  • VPI_IMAGE_FORMAT_NV12
  • VPI_IMAGE_FORMAT_NV12_BL
• The following boundary conditions are accepted.
  • VPI_BOUNDARY_COND_ZERO
  • VPI_BOUNDARY_COND_CLAMP

CPU

• Do not accept VPI_IMAGE_FORMAT_NV12_BL.

CUDA

• Only accepts the following image formats:
  • VPI_IMAGE_FORMAT_U8
  • VPI_IMAGE_FORMAT_S8
  • VPI_IMAGE_FORMAT_U16
  • VPI_IMAGE_FORMAT_S16
  • VPI_IMAGE_FORMAT_RGBA8
  • VPI_IMAGE_FORMAT_BGRA8
  • VPI_IMAGE_FORMAT_NV12

VIC

• Only available on Jetson devices.
• Only accepts the following image formats:
  • VPI_IMAGE_FORMAT_RGBA8
  • VPI_IMAGE_FORMAT_BGRA8
  • VPI_IMAGE_FORMAT_NV12
  • VPI_IMAGE_FORMAT_NV12_BL
• Only accepts the following interpolators:
  • VPI_INTERP_LINEAR
  • VPI_INTERP_LINEAR_FAST (same implementation as linear)

PVA

• Not implemented

Performance

For information on how to use the performance table below, see Algorithm Performance Tables.
Before comparing measurements, consult Comparing Algorithm Elapsed Times.
For further information on how performance was benchmarked, see Performance Measurement.

clear filters Device: Jetson AGX Xavier Jetson TX2 Jetson Nano  -  Streams: 1 4 8

References

• Daniel Ruijters, Bart M. ter Romeny, Paul Suetens (2008) "Efficient GPU-Based Texture Interpolation using Uniform B-Spline"
  Journal of Graphics Tools, 13:4 61-69.