The Heal node can reconstruct damaged, low res, or 8-bit data with 16-bit, high resolution fidelity. The Heal node can take quantized images with extreme banding of any shape, and clean up the terrain into a naturalistic output.
Heal can consume 8-bit data, (visually) damaged images, or low quality satellite data — even with bad JPEG artifacts — and turn it into a reasonably clean heightfield. It is also useful for upscaling lower resolution data such as Google map extracts.
Obviously, not all data can be reconstructed, but you can get a fair bit of quality back. Below is an example where we downsample a 16-bit heightfield to 8-bit, and then reconstruct it using the Heal node.
// TODO: Image
|Level||The level of healing to apply to the data.|
|Advanced||Enables additional options.|
|Softness||The softness of the reconstruction features.|
|Iterations||The number of times the reconstruction process is applied. Use lower values for Level and Softness with higher iterations for more refined results.|
|Enable Parallel Processing||Enable multi-CPU processing of the effect.|
|Chunk Size||The chunk size into which the image is divided for processing.|
|Edge Blending||The percentage of blending between the edges of neighboring chunks. Higher values require more memory and processing time.|
If you see grid-like artifacts in your output, use higher values for Edge Blending. If that does not help, try increasing Chunk Size. If either does not help, you can disable Parallel Processing. This may result in slower builds, but the result will be accurate and error free.