Robust Contrast Adaptive Sharpening (RCAS) Based on the following implementation: https://github.com/GPUOpen-Effects/FidelityFX-FSR2/blob/ea97a113b0f9cadf519fbcff315cc539915a3acd/src/ffx-fsr2-api/shaders/ffx_fsr1.h#L672 RCAS is based on the following logic. RCAS uses a 5 tap filter in a cross pattern (same as CAS), W b W 1 W for taps d e f W h Where ‘W’ is the negative lobe weight. output = (W*(b+d+f+h)+e)/(4W+1) RCAS solves for ‘W’ by seeing where the signal might clip out of the {0 to 1} input range, 0 == (W(b+d+f+h)+e)/(4W+1) -> W = -e/(b+d+f+h) 1 == (W(b+d+f+h)+e)/(4*W+1) -> W = (1-e)/(b+d+f+h-4) Then chooses the ‘W’ which results in no clipping, limits ‘W’, and multiplies by the ‘sharp’ amount. This solution above has issues with MSAA input as the steps along the gradient cause edge detection issues. So RCAS uses 4x the maximum and 4x the minimum (depending on equation)in place of the individual taps. As well as switching from ‘e’ to either the minimum or maximum (depending on side), to help in energy conservation. This stabilizes RCAS. RCAS does a simple highpass which is normalized against the local contrast then shaped, 0.25 0.25 -1 0.25 0.25 This is used as a noise detection filter, to reduce the effect of RCAS on grain, and focus on real edges. The CAS node runs after tonemapping, so the input will be in the range of 0 to 1.