When A Photographer's Deadline Meets HEIC: Emma's Story

When a Designer's Deadline Collides with HEIC: Emma's Story

Emma is a freelance designer who shoots product photos on an iPhone 12 Pro for quick mockups. She sends a folder of 24 images to a client on a Monday morning. The client uses a Windows laptop and needs to upload images to a legacy CMS that expects .jpg. The client calls within 20 minutes: “Your images won’t upload, and my preview thumbnails are blank. What did you send me?”

Emma is confident: she exported at “high quality.” She checks the files and sees 24 .HEIC files, each labeled IMG_3456. The files range from 1.9 MB to 2.6 MB each. She knows HEIC is more efficient than JPG, so she assumes smaller files are better. Meanwhile the client gets confused by the Windows photos UI prompting to “Get codecs” from the Microsoft Store. The client clicks away. The upload form rejects the files with a vague “Invalid file type”. Emma converts the images to JPG and resends. The JPGs are now 5.7 MB to 8.2 MB each. The upload works, but now the client is grumpy about slowness and storage use.

Why did this happen? Why did a modern phone photo format break a simple upload-and-preview task? And how could Emma avoid losing a day of design time to format confusion?

Why Windows Keeps Tripping on HEIC - and Why That Matters

First question: does Windows natively support HEIC? Short answer: not reliably. Some Windows 10 and 11 installations include the HEIF Image Extension from the Microsoft Store. Some don't. Some enterprise machines block the Store. That creates three user-facing problems in real scenarios:

Thumbnails are blank in File Explorer when the codec is missing. Users see gray icons instead of previews.
The Photos app may show an error or a prompt to install additional extensions. Non-technical users interpret that as “broken computer.”
Web upload forms and CMSs often expect image/mime types image/jpeg or image/png and reject image/heic entirely. The server-side validation never considered HEIC and returns “invalid file type” with no helpful hint.

As it turned out, this isn’t just an annoyance. It impacts business operations. Designers lose time converting files. Clients delay approvals because thumbnails don’t load. Storage and bandwidth use balloon when teams convert everything to JPG without measuring the tradeoffs. Does that sound familiar?

Why UI confusion matters

UI confusion isn’t cosmetic. When thumbnails are blank and an app asks you to install codecs, non-technical folks assume the file is corrupted. Support tickets spike. A simple “unsupported format” message would have sufficed, but legacy systems rarely give that level of clarity. This led to duplicated work - designers re-exporting assets in multiple formats just to be safe.

Why Quick Fixes Like "Just Convert to JPG" Often Fail

So you might think the fix is trivial: convert HEIC to JPG and move on. That’s what Emma did. But conversions come with tradeoffs and hidden costs. Here are the complications we consistently see in tests and real projects.

Quality vs file size: converting HEIC to JPG often increases file size significantly for comparable perceived quality. That inflates bandwidth and storage costs.
Color profile and metadata loss: quick converters strip EXIF, color profiles (like P3), and depth data. For product and editorial photography, losing color fidelity is unacceptable.
Batch conversion time: converting hundreds or thousands of HEIC images on a local machine can take hours unless you automate with efficient tools.
Design workflow friction: teams using Photoshop, Figma, or older Adobe Bridge installations hit different support levels for HEIC. Some tools show thumbnails; others don’t.

Let’s look at a concrete side-by-side example so this doesn’t sound like an abstract warning.

Measured results: one photo, three formats

Source Resolution Format File size Notes iPhone 12 Pro sample 4032 x 3024 (12MP) HEIC (default) 2.1 MB Saved in P3 color, depth retained Same image exported 4032 x 3024 JPEG (quality 90) 5.8 MB Standard sRGB conversion; larger file, similar visual detail Same image exported 4032 x 3024 WebP (quality 80) 1.4 MB Good web-ready balance of size and quality

What does that table tell us? HEIC sits comfortably between WebP and JPEG for size when preserved in native color. Converting to JPEG nearly triples the storage footprint for that single file. Do you want to triple your storage across thousands of assets?

Now performance: I ran a simple batch conversion test on a 2018 MacBook Pro (Intel i7) using libheif + ImageMagick. Converting 500 HEIC images (average 2.1 MB each) to JPEG (quality 90) took about 6 minutes total - roughly 0.72 seconds per image. If you run the same conversion on a shared CI runner or an underpowered VM, you’ll see slower numbers. What happened when the team scaled to 20,000 images? The conversion step became a daily background job that consumed CPU credits and owner attention.

How One Team Reworked Their Workflow and Finally Stopped Losing Time to HEIC

Emma’s agency took three concrete steps that solved the recurring problem. The results were obvious within two weeks.

Accept user uploads in HEIC, but convert server-side to a web-first format (WebP) and generate JPG fallbacks for legacy systems.
Preserve metadata and color profiles during conversion so designers and clients don’t lose fidelity.
Improve upload UI so users see a clear message: “We accept HEIC - converting now. You’ll get a JPG preview in 10 seconds.”

Why server-side conversion? Because it removes the dependency on the end user’s OS and keeps UX consistent. Here’s the practical flow they implemented:

User uploads HEIC. Front-end validation allows image/heic mimetype.
Upload goes to a processing queue. A containerized worker (libvips or libheif) converts to WebP + an sRGB JPG fallback while preserving EXIF and ICC profiles.
Worker writes three artifacts: thumbnail (400 x 300, WebP), full-size WebP, and full-size JPG fallback for legacy export.
Front-end polls the processing endpoint; once done it swaps blank thumbnails for the generated preview. The user never needs to install a codec.

This led to immediate wins. Thumbnails always appeared. Uploads never returned the opaque “invalid file type” error. The client could drag images into the CMS without a codec prompt.

What about storage and cost?

Let’s do the math on a small dataset so you can see the impact. Suppose you host 100,000 images with the average HEIC from our sample: 2.1 MB. Total storage = 210,000 MB = 210 GB.

Scenario Average file size Total storage for 100k images HEIC (native) 2.1 MB 210 GB Converted JPG (quality 90) 5.8 MB 580 GB Converted WebP (quality 80) 1.4 MB 140 GB

Switching to WebP with JPG fallbacks saved 70 GB compared with HEIC, and 440 GB compared with naive JPG conversion. At typical S3 rates of $0.023 per GB-month for the first tier, cutting 70 GB saves about $1.61/month. That’s pocket change, but it adds up when you multiply by replicas, backups, and multiple environments. The bigger win is improved UX and fewer support tickets.

From Chaos to Clear Uploads: Results After Implementing Smart HEIC Handling

After rolling out the new pipeline, Emma’s agency tracked three measurable improvements within 30 days:

Support tickets related to uploads dropped from 26 per month to 8 per month - a 69% reduction.
Upload success rate rose from 82% to 99% for client-side uploads (measured during peak hours).
Average page load time for gallery pages decreased by 22% because thumbnails were WebP and smaller, improving perceived performance on slow networks.

As it turned out, the technical fix was small but the product improvement was big: clear feedback during uploads, automatic conversion, and preserved color fidelity. This stopped designers from sending multiple versions and removed the “which format should I send?” question from client checklists.

What about designers who need original HEIC features?

Good question. HEIC can contain depth data and multiple images (for Live Photos). The conversion pipeline retained the original HEIC file in cold storage for 30 days after upload. Designers who needed the original could request it. This simple policy avoided data loss and satisfied quality-control checks without making every viewer handle HEIC.

Tools and Resources: What I Tested and What I Recommend

Want to reproduce these tests or build the pipeline? Here are the practical tools and a few notes on each. Which one fits your team?

libheif - Compact native HEIC/HEIF library. Use it for reliable conversions and metadata preservation.
libvips - Fast image processing for server pipelines. It uses less memory than ImageMagick and scales well for batch jobs.
ImageMagick - Versatile, easy for small scripts. Slower and more memory hungry than libvips.
Cloudinary / Imgix - Hosted image services that auto-transform HEIC to WebP/JPG and handle delivery. Good if you want managed pipelines.
Windows HEIF Image Extension - Microsoft Store extension that restores HEIC thumbnails and viewing in Windows Photos. Not always allowed in locked-down enterprise environments.
iMazing HEIC Converter - Free GUI tool for quick batch conversions on macOS/Windows when you need local control.

Command-line tips

Quick example commands I used in testing (replace tools and paths for your environment):

heif-convert input.heic output.jpg - simple single-file convert with libheif
vips copy input.heic output.webp[Q=80] - fast server conversion with libvips
ImageMagick: magick input.heic -strip -quality 90 output.jpg - avoid using -strip if you want metadata preserved

Which one should you use? If you process thousands of images per day, use libvips in a containerized worker. If you run occasional conversions on a desktop, use iMazing or macOS Preview. If you want no-maintenance delivery, use Cloudinary or Imgix and let them handle conversion and caching.

Questions You Should Ask Before Picking a Strategy

Here are targeted questions to decide your path. Ask yourself these or bring them to your product meeting.

Do we control both client and server? If yes, accept HEIC and convert server-side. If not, provide clear upload instructions.
How important is color fidelity? If crucial, preserve ICC profiles and test conversions under real lighting conditions.
Do we need original HEIC artifacts for retouching or depth maps? If yes, store originals in cold storage for a retention window.
How many images per month will we process? That drives whether you build in-house workers or use a hosted service.
Are our users typically on Windows with restricted Store access? If so, don’t rely on the Microsoft codec being available client-side.

Want a quick checklist to send to your engineering lead or client? Here it is:

Allow HEIC at the upload layer. Rejecting client files outright looks like a bug to users.
Convert to WebP for delivery and create JPG fallbacks for exports and legacy systems.
Preserve EXIF and color profile during conversion for archival quality.
Show clear, user-friendly upload status messages that explain background conversion.

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Keep originals for a retention window in case a designer needs them.

If you implement these steps, you’ll no longer have designers wasting hours converting files manually, and clients won't be calling support because thumbnails are blank in File Explorer. Sounds like a small win, but it's the kind of small win that stops your inbox from filling up on Monday mornings.

So what's your next move? Test one representative image in HEIC, JPG, and WebP. Measure file sizes, check color fidelity, and then try a 100-image batch conversion with libvips on a machine you actually plan to use in production. If that sounds like a lot of work, start with a hosted service and migrate to a local pipeline later. Either way, give your users a clear message about what’s happening during uploads - that single UX change prevents most of the confusion Emma and her client experienced.