Radeon ProRender

Viewport Render Properties

The viewport render properties allow you to tune the appearance of the render output produced.

To access the render properties, in the top right corner of the Viewport, click the icon that toggles the post effect and render properties display. Note that each time you change the render properties in the Viewport, you should perform the scene rendering afresh. For details, see Viewport Render.

The Viewport render properties and post effects are grouped as follows.


Tone mapping is a technique used in image processing and computer graphics to map one set of colors onto another to approximate the appearance of HDR images in a medium that has a more limited dynamic range (for details, see Tone Mapping).

AMD Radeon ProRender offers the following tonemapping parameters:

  • Sensitivity describes how much light is let into the image.
  • Exposure controls how long the shutter stays open to let the light in.
  • FStop is the aperture width which works just as the aperture of a regular camera: the smaller the value, the wider the aperture and the more light is transmitted onto the film.

White Balance

The White Balance parameter works just as the basic setting of the same name in a digital camera letting you set the color temperature of the light in the image. Supported values are from 1000 (for a cool blue tint) to 40000 (for a warm red tint). A value of 6500 is considered the white point.

Gamma Correction

The Display Gamma parameter allows you to apply a gamma correction for the output image to appear correctly on the monitor. The default gamma correction value is 2.2. A value of 1 means that gamma is not corrected.

Render Settings

The Raycast Epsilon parameter allows you to change the raycast epsilon value directly in the Viewport. For further details on this parameter, see Advanced Quality Settings.


In the Denoiser section, you can choose to apply a denoiser filter to detect noisy pixels in the render output and reconstruct their color.

You can choose between the following denoising filters:

  • Bilateral filter is a noise reducing filter that blends neighboring pixels while preserving sharp edges.

    The filter works by replacing each pixel with a weighted average of its neighbors. The weighted average is calculated based on several factors, including pixel color similarity, spatial proximity, normal differences and object ID values. This ensures that only similar pixels contribute to the resulting color, which makes it possible to produce high-quality smoothing without blurring object contours.

  • Machine Learning filter is an AI-accelerated filter that has been trained on large data sets. It uses deep machine learning to remove noise from rendered images.


Although the denoiser allows you to keep sampling and render time low, do not consider it a magic wand. The decision whether to use the denoiser or nor, and which filter to choose, will most likely depend on the project. Note also that the denoiser will perform better with more samples.