Inline Image Previews with Sharp, BlurHash, and Lambda Functions
Mar 13, 2025 am 10:20 AMWebsite and web app loading often suffers from content reflow: images load after the surrounding content, causing jarring shifts in layout. This frustrating user experience can be mitigated. While React's Suspense offers a solution, it sacrifices performance by delaying all content until images are fully loaded. A better approach? Displaying blurry image previews immediately, seamlessly replaced by the high-resolution images upon loading.
Progressive JPEGs might seem like the answer, offering blurry initial rendering followed by gradual refinement. However, even progressive JPEGs require a wait for initial data, leading to that same initial content reflow.
This article explores two alternative methods: creating custom blurry previews and leveraging BlurHash.
Libraries Used:
- Jimp (version 0.16.1)
- BlurHash (version 1.1.5)
- Sharp (version 0.30.3)
Method 1: Generating Custom Previews
Instead of relying on image URLs, we can embed Base64-encoded, low-quality, blurry image previews directly into our JavaScript. While Base64 encoding typically leads to large file sizes, a small, blurry preview remains manageable. This preview is displayed immediately, replaced by the high-resolution image once loaded.
The following resizeImage
function (simplified for brevity) uses Jimp to create a blurry preview:
function resizeImage(src, maxWidth, quality) { return new Promise(res => { Jimp.read(src, async function (err, image) { if (image.bitmap.width > maxWidth) { image.resize(maxWidth, Jimp.AUTO); } image.quality(quality); const previewImage = image.clone(); previewImage.quality(25).blur(8); const preview = await previewImage.getBase64Async(previewImage.getMIME()); res({ STATUS: "success", image, preview }); }); }); }
This preview, while not tiny, is significantly smaller than the original image. The corresponding React code (simplified) handles displaying the preview and swapping it with the full-resolution image:
// ... React component code ...
Method 2: Improving with BlurHash (and a better alternative)
While initially suggested, BlurHash, while generating extremely small previews via Base83 encoding, requires client-side JavaScript and <canvas></canvas>
tags, making it less ideal for server-side rendering (SSR) frameworks like Next.js and SvelteKit.
A superior alternative is Plaiceholder. It utilizes Sharp, requiring similar Lambda installation considerations as described later, but generates tiny base64 previews. By tracking the image's dimensions and applying a blur filter, it achieves results comparable to BlurHash, while being fully SSR-friendly. The preview can be displayed under the real image using CSS, providing a seamless transition.
Original BlurHash Implementation (Less Recommended):
The Sharp library can generate BlurHash previews. For AWS Lambda deployment, use this installation command:
"install-deps": "npm i && SHARP_IGNORE_GLOBAL_LIBVIPS=1 npm i --arch=x64 --platform=linux sharp"
The following function generates the BlurHash preview:
import { encode, isBlurhashValid } from "blurhash"; const sharp = require("sharp"); export async function getBlurhashPreview(src) { // ... (Sharp processing and BlurHash encoding) ... }
The PreviewCanvas
component then decodes and renders the BlurHash preview using the Canvas API.
Conclusion:
Preventing content reflow during image loading enhances user experience. Generating custom blurry previews or using Plaiceholder offers a balance between performance and visual smoothness, providing a superior alternative to simply delaying content rendering until all images are loaded. Choose the method that best suits your project's needs and framework.
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