This is another post of the series where I explain some ideas I tried in order to improve the upscaling of the half-resolution SSAO render target of the VKDF sponza demo that was written by Iago Toral. In the previous post, I had classified the sample neighborhoods in surface neighborhoods and neighborhoods that contain depth discontinuities using the normals. Having this information about the neighborhoods, in this post, I will try to further improve the nearest depth algorithm (see also parts 1 and 2) and reduce the artifacts in the neighborhoods where we detect depth discontinuities.
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 . 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: