Multi-Level Bilateral Upsampling on The GPU =========================================== This function implements a multi-level bilateral filtering technique for joint bilateral upsampling. This technique upsamples a low-resolution image \(e.g., motion vectors\) using a high-resolution guide image \(the image itself, color buffer, depth buffer\) while preserving edges. It combines information from the low-resolution image and a downsampled version of the high-resolution guide. .. seealso:: Riemens, B., Gangwal, O.P., Barenbrug, B., & Berretty, R. \(2009\). Multistep joint bilateral depth upsampling. Electronic imaging. https://www.semanticscholar.org/paper/Multistep-joint-bilateral-depth-upsampling-Riemens-Gangwal/1ddf9ad017faf63b04778c1ddfc2330d64445da8 Multi-Level Bilateral Filtering ------------------------------- Joint bilateral upsampling effectively transfers details from a high-resolution guide to a low-resolution image. However, using a single guide level can lead to artifacts, especially around sharp edges. Multi-level bilateral filtering addresses this by incorporating information from a downsampled version of the guide, providing a broader context for the filtering process. This results in smoother upsampling with better edge preservation. .. code-block:: none :caption: Joint Bilateral Upsampling /* This is a function used for Joint Bilateral Upsampling implemented in HLSL. Inspired by Riemens et al. (2009). --- Riemens, B., Gangwal, O.P., Barenbrug, B., & Berretty, R. (2009). Multistep joint bilateral depth upsampling. Electronic imaging. https://www.semanticscholar.org/paper/Multistep-joint-bilateral-depth-upsampling-Riemens-Gangwal/1ddf9ad017faf63b04778c1ddfc2330d64445da8 */ float4 JointBilateralUpsample( sampler Image, // This should be 1/2 the size as GuideHigh sampler GuideLow, // This should be 1/2 the size as GuideHigh sampler GuideHigh, // This should be 2/1 the size as Image and GuideLow float2 Tex ) { // Initialize variables float2 PixelSize = ldexp(fwidth(Tex.xy), 1.0); float4 GuideHighSample = tex2D(GuideHigh, Tex); float4 BilateralSum = 0.0; float4 WeightSum = 0.0; [unroll] for (int dx = -1; dx <= 1; ++dx) { [unroll] for (int dy = -1; dy <= 1; ++dy) { // Calculate offset float2 Offset = float2(float(dx), float(dy)); float2 OffsetTex = Tex + (Offset * PixelSize); // Sample image and guide float4 ImageSample = tex2Dlod(Image, float4(OffsetTex, 0.0, 0.0)); float4 GuideLowSample = tex2D(GuideLow, OffsetTex); // Calculate weight float3 Delta = GuideLowSample.xyz - GuideHighSample.xyz; float DotDD = dot(Delta, Delta); float Weight = (DotDD > 0.0) ? 1.0 / DotDD : 1.0; BilateralSum += (ImageSample * Weight); WeightSum += Weight; } } return BilateralSum / WeightSum; } Self-Guided Optimization ------------------------ In the original multi-level bilateral filtering approach, the spatial weight is calculated using the difference between the high-resolution guide and its downsampled version. However, in scenarios where the low-resolution image and the downsampled guide share similar properties \(e.g., when the guide is derived from the image itself\), we can simplify the process by directly using the low-resolution image for calculating the spatial weight. This modification eliminates the need for an explicit downsampled guide and can improve performance by reducing texture fetches. Using the image as a guide, we maintain the edge-preserving characteristics while optimizing the computation. .. code-block:: none :caption: Self-Guided Bilateral Upsampling float4 BilateralUpsampleXY( sampler Image, // This should be 1/2 the size as GuideHigh sampler Guide, // This should be 2/1 the size as Image and GuideLow float2 Tex ) { // Initialize variables float2 PixelSize = ldexp(fwidth(Tex.xy), 1.0); float4 GuideHighSample = tex2D(Guide, Tex); float4 BilateralSum = 0.0; float4 WeightSum = 0.0; [unroll] for (int dx = -1; dx <= 1; ++dx) { [unroll] for (int dy = -1; dy <= 1; ++dy) { // Calculate offset float2 Offset = float2(float(dx), float(dy)); float2 OffsetTex = Tex + (Offset * PixelSize); // Calculate the difference and normalize it from FP16 range to [-1.0, 1.0) range // We normalize the difference to avoid precision loss at the higher numbers float4 ImageSample = tex2Dlod(Image, float4(OffsetTex, 0.0, 0.0)); // Calculate weight float2 Delta = CMath_Float2_FP16ToNorm(ImageSample.xy - GuideHighSample.xy); float DotDD = dot(Delta, Delta); float Weight = (DotDD > 0.0) ? 1.0 / DotDD : 1.0; BilateralSum += (ImageSample * Weight); WeightSum += Weight; } } return BilateralSum / WeightSum; }