The Adaptive Sampling parameter is a rendering option that disables sampling for pixels that reach a specified noise threshold, which allows the kernel to focus its processing on areas that still need refinement. The Adaptive Sampling options are found in the Octane Kernel rollout for the Direct Light, Path Tracing, and Photo Tracing kernels.

Figure 1: The Adaptive Sampling options.

Parameters

    • Adaptive Sampling - Stops sampling pixels that reach a specified noise threshold, which allows the kernel to focus its processing on areas that still need refinement.
    • Noise Threshold - When Adaptive Sampling is enabled, Noise Threshold specifies the smallest relative noise level. When the noise estimate of a pixel becomes less than this value, sampling switches off for this pixel. Good values are in the range of 0.01 - 0.03. The default is 0.02, which is pretty clean.
    • Min. Adaptive Samples - Specifies the minimum samples to calculate before Adaptive Sampling kicks in. The reason for this option is the fact that the noise estimate of a pixel is just an estimate with a large initial error. The higher you set the noise threshold, the higher you should also set Min. Adaptive Samples to avoid artifacts.
    • Pixel grouping - When Adaptive Sampling is enabled, Pixel Grouing specifies the number of pixels that are handled together. When all pixels of a group have reached the noise level, sampling will stop for all of these pixels.
    • Expected Exposure - This parameter should be about the same value as the image exposure, or 0 (the default value) to ignore these settings. This parameter is used by Adaptive Sampling to determine the pixels that are bright and those that are dark - which depends on the exposure setting in the Octane Imager. If the value is not 0, Adaptive Sampling reduces the noise estimate of very dark areas of the image. It also will also increase the Min. Adaptive Samples limit for very dark areas, because very dark areas tend to find paths to light sources irregularly, resulting to an otherwise over-optimistic noise estimate.