Depth-aware upsampling experiments (Part 3.1: Improving the upsampling using depths to classify the samples)

In my previous posts of these series I analyzed the basic idea behind the depth-aware upsampling techniques. In the first post [1], I implemented the nearest depth sampling algorithm [3] from NVIDIA and in the second one [2], I compared some methods that are improving the quality of the z-buffer downsampled data that I use with the nearest depth. The conclusion was that the nearest depth sampling alone is not good enough to reduce the artifacts of Iago Toral’s SSAO implementation in VKDF [4] to an acceptable level. So, in this post, I am going to talk about my early experiments to further improve the upsampling and the logic behind each one. I named it part 3.1 because while having started the series I’ve found that some combinations of these methods with other ones can give quite better visual results, and as my experiments with the upsampling techniques cannot fit one blog post, I am going to split the upscaling improvements (part 3) in sub-parts.

Continue reading Depth-aware upsampling experiments (Part 3.1: Improving the upsampling using depths to classify the samples)

Depth-aware upsampling experiments (Part 1: Nearest depth)

This post is about different depth aware techniques I tried in order to improve the upsampling of the low resolution Screen Space Ambient Occlusion (SSAO) texture of a VKDF demo. VKDF is a library and collection of Vulkan demos, written by Iago Toral. In one of his demos (the sponza), Iago implemented SSAO among many other graphics algorithms [1]. As this technique is expensive, he decided to optimize it by using lower resolution textures and render target, which he then upsampled to create a full resolution image that he blended with his original one to display the result. For the upsampling he used linear interpolation, and as expected he observed many artifacts that were increasing by lowering the SSAO textures resolution.

Some time ago, I started experimenting with methods to improve that upsampling in order to familiarize myself with Vulkan. The most promising ones seemed to be the depth-aware techniques:

Continue reading Depth-aware upsampling experiments (Part 1: Nearest depth)