Recreating lens effects with WebGPU image shaders 2025 — Optimization guide for low-power devices

Published: Sep 29, 2025 · Reading time: 4 min · By Unified Image Tools Editorial

WebGPU is stable across major browsers in 2025, eliminating the need for heavyweight WebGL stacks to ship image effects. The question for web engineers is how to deliver rich lens treatments (flares, depth of field, glow) without torching performance or battery life. This guide walks through compute + render pipelines that keep 60 fps on low-power devices, plus the optimization tactics that make it sustainable.

TL;DR

  • Two-stage rendering: split into (1) compute pass for light-blocker extraction and (2) render pass for compositing + blur.
  • Tile-based downsampling: compute flares at quarter resolution and interpolate via mix during composition.
  • Adaptive sampling: adjust sample counts using navigator.gpu.getPreferredCanvasFormat() and Battery API signals.
  • GPU/CPU telemetry: push WebGPU timestamp-query data into performance-guardian to monitor frame costs.
  • Accessibility safeguards: honor prefers-reduced-motion and provide a static image fallback.

Pipeline overview

graph LR
    A[Source Texture] --> B[Compute Shader: Bright Spot Detection]
    B --> C[Compute Shader: Flare Tile Accumulation]
    C --> D[Render Pass: Bokeh & Bloom]
    D --> E[Post Processing: Tone Mapping]
    E --> F[Canvas / Texture Output]

Bootstrapping WebGPU

const adapter = await navigator.gpu.requestAdapter({ powerPreference: 'low-power' })
const device = await adapter?.requestDevice({
  requiredFeatures: ['timestamp-query'],
  requiredLimits: { maxTextureDimension2D: 4096 }
})
const context = canvas.getContext('webgpu')!
context.configure({
  device,
  format: navigator.gpu.getPreferredCanvasFormat(),
  alphaMode: 'premultiplied'
})

If timestamp-query is unavailable, fall back to CPU timers.

Bright-spot extraction shader

// shaders/bright-spot.wgsl
@group(0) @binding(0) var<storage, read> inputImage: array<vec4<f32>>;
@group(0) @binding(1) var<storage, read_write> brightMask: array<f32>;

@compute @workgroup_size(16, 16)
fn main(@builtin(global_invocation_id) global_id: vec3<u32>) {
  let idx = global_id.y * textureWidth + global_id.x;
  if (idx >= arrayLength(&inputImage)) { return; }
  let color = inputImage[idx];
  let luminance = dot(color.rgb, vec3<f32>(0.299, 0.587, 0.114));
  brightMask[idx] = select(0.0, luminance, luminance > params.threshold);
}

Expose params.threshold via UI sliders so designers can tweak the look.

Tile accumulation

// shaders/flare-accumulate.wgsl
@group(0) @binding(0) var<storage, read> brightMask: array<f32>;
@group(0) @binding(1) var<storage, read_write> flareTiles: array<vec4<f32>>;

@compute @workgroup_size(8, 8)
fn main(@builtin(workgroup_id) group_id: vec3<u32>) {
  let tileIndex = group_id.y * tileCountX + group_id.x;
  var sum = vec4<f32>(0.0);
  for (var y = 0u; y < TILE_SIZE; y = y + 1u) {
    for (var x = 0u; x < TILE_SIZE; x = x + 1u) {
      let idx = (group_id.y * TILE_SIZE + y) * textureWidth + (group_id.x * TILE_SIZE + x);
      sum += vec4<f32>(brightMask[idx]);
    }
  }
  flareTiles[tileIndex] = sum / f32(TILE_SIZE * TILE_SIZE);
}

Use tile sizes between 16 and 32; on low-end devices you can shrink resolution further to save power.

Compositing in the render pass

// pipeline/render.ts
const flarePipeline = device.createRenderPipeline({
  vertex: { module: device.createShaderModule({ code: quadVert }) },
  fragment: {
    module: device.createShaderModule({ code: flareFrag }),
    targets: [{ format: contextFormat }]
  },
  primitive: { topology: 'triangle-list' }
})

const pass = commandEncoder.beginRenderPass({
  colorAttachments: [{
    view: context.getCurrentTexture().createView(),
    loadOp: 'load',
    storeOp: 'store',
    clearValue: { r: 0, g: 0, b: 0, a: 1 }
  }]
})

The fragment shader mixes bloom and bokeh textures.

// shaders/flare.frag.wgsl
@group(0) @binding(0) var flareSampler: sampler;
@group(0) @binding(1) var flareTexture: texture_2d<f32>;
@group(0) @binding(2) var blurTexture: texture_2d<f32>;

@fragment
fn main(@builtin(position) pos: vec4<f32>) -> @location(0) vec4<f32> {
  let uv = pos.xy / vec2<f32>(canvasSize);
  let flare = textureSample(flareTexture, flareSampler, uv);
  let blur = textureSample(blurTexture, flareSampler, uv);
  return mix(flare, blur, params.blurMix) * params.intensity;
}

Power and performance tuning

  • Resolution scaling: derive render resolution from device.limits.maxTextureDimension2D and window.devicePixelRatio.
  • Workgroup throttling: when battery drops below 20%, halve workgroup counts.
  • Uniform updates: skip per-frame uniform uploads unless UI changes.
  • Timestamp reads: use writeTimestamp and alert if GPU time exceeds 5 ms.
const querySet = device.createQuerySet({ type: 'timestamp', count: 2 })
passEncoder.writeTimestamp(querySet, 0)
// ... render operations ...
passEncoder.writeTimestamp(querySet, 1)

Accessibility and fallbacks

If prefers-reduced-motion: reduce is set, serve a static PNG instead of the animated canvas.

.hero-visual {
  background-image: url('/images/hero-static.png');
}

@media (prefers-reduced-motion: no-preference) {
  .hero-visual {
    background-image: none;
    canvas { display: block; }
  }
}

Cache the static asset in your PWA so offline users see a consistent hero.

Monitoring and experimentation

Track these metrics with performance-guardian:

MetricTargetAction
GPU frame time< 6 msTune workgroup sizes
Battery drain (5 min avg)< 2%Lower resolution scale
LCP variance±100 msFallback to static imagery
CTR+5%Graduate the effect if conversion improves

Checklist

  • [ ] Fallback exists for non-WebGPU environments.
  • [ ] Compute and render passes are decoupled.
  • [ ] GPU costs are visible via timestamp-query.
  • [ ] prefers-reduced-motion is honored.
  • [ ] Battery API adjusts quality under low power.
  • [ ] CTR and LCP are monitored via RUM.

Summary

WebGPU lets you build sophisticated lens effects with lightweight shaders. Combine tile-based computation and resolution scaling to keep 60 fps on modest devices. Measure visuals alongside battery and LCP impact so your production rollouts balance delight with performance.

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