How to Remove Glare from Product Photos (Without Ruining the Texture)
Written by Naman Kasliwal Co-founder & CEO of Kaptured.AI
Glare is the silent killer of ecommerce product photography. A single hotspot on a watch face, a window reflection on a lacquered handbag, an over-bright spot on a gemstone: each one shifts the product from “ready to ship” to “ready to be rejected by Amazon’s QA bot”.
This guide covers the three approaches that work in production: AI-first cleanup, traditional Photoshop techniques, and prevention at the shoot. We’ll cover which one fits which catalogue, because the right approach depends on your catalogue size, brand, and budget.
Why glare gets listings rejected
Amazon’s main-image rules are explicit: pure white background, product fills 85% of the frame, no props or text. Implicit in these rules is “no distortion that prevents the customer from evaluating the product”. Hotspots violate this. So do plastic-wrap shines, window reflections, and lens flares.
Zalando sets similar standards, as do Myntra, Nykaa, Meesho and Ajio for brands selling in India. Brands that ship glare-ridden imagery either lose ranking or get listings rejected.
The conversion impact is even more direct. Customers can’t see the product’s colour, can’t judge the texture, can’t tell the actual finish. Hotspots are the digital equivalent of a smudge on a window display.
Approach 1: AI-first glare removal
The fastest, cheapest path for any brand working at catalogue scale.
How it works:
- Start from the source image.
- The brightest hotspots are detected: lens flares, window reflections, studio overlights, and plastic-wrap shines.
- The texture under each hotspot is rebuilt to match the surrounding fabric grain, metal lustre, or material finish.
- The image is exported at marketplace-compliant resolution.
What makes it work is texture-aware reconstruction. Generic cleanup “smooths over” hotspots and flattens the surface: the metal looks plastic, the leather looks like paper, the gem loses its fire. Done well, AI glare removal separates the unwanted hotspot from the product’s natural shine and removes only the hotspot.
The economics matter. A skilled Photoshop retoucher costs $15-$50 per image at typical production rates, so a 500-SKU catalogue refresh runs $7,500-$25,000 by hand. AI cleanup costs a small fraction of that, and the whole refresh is delivered in days.
For jewelry catalogues, the change is bigger still. Polished metals and faceted gems are the hardest categories to shoot cleanly: sunlight bouncing off a diamond, overlights catching the bezel of a watch, a flare from a single point source on a polished ring. AI cleanup removes a QA bottleneck that used to need cross-polarised lighting or a dedicated retoucher.
Approach 2: Traditional Photoshop or Lightroom
The standard Photoshop workflow:
- Open the source image at full resolution.
- Use the Clone Stamp with a small brush, sampling matched texture from a clean adjacent area.
- For larger hotspots, use Content-Aware Fill to suggest a fill, then refine with Clone Stamp.
- Set the layer’s blend mode to “Darken” so it only affects pixels brighter than the sample.
- Use Adjustment Layers (Curves, Selective Color) to balance the surrounding area.
- Export with the sharpening the destination channel needs.
This gives a retoucher control over every pixel, but it is slow. A skilled retoucher handles 20-40 images per day depending on complexity. For a catalogue refresh of any meaningful size, the time and cost rule it out as the main workflow.
Approach 3: Prevention at the shoot
The best glare removal is the kind you never have to do.
Cross-polarisation is the classic fix for glossy products. A polarising filter on the light source plus one on the lens, set at perpendicular orientations, kills almost all surface reflections. It is used widely in jewelry, watch, electronics, and polished-leather photography.
Bounce lighting reduces hotspots by softening the light source. A large softbox or scrim spreads the overlight into a wider, gentler source, so hotspots become smooth gradients instead of pinpoint blowouts.
Dulling spray gives the product a temporary matte coating that absorbs reflection, and wipes off after the shoot.
These techniques work, but they need a studio, lighting kit and production time for every setup. At catalogue scale that setup cost makes them slower and dearer than AI-first cleanup.
Which approach fits which catalogue
- Apparel and fashion: AI-first. Glare is rare on most fabrics, and when it appears (satin, sequins, metallics) AI cleanup handles it cleanly.
- Jewelry: AI-first. The volume of macro work and the number of hotspots make any other approach uneconomical at scale. See our jewelry photoshoots.
- Footwear: AI-first, with extra care on premium leather where the finish has to read exactly right.
- Packaged goods: AI-first. Plastic wrap and glossy labels are predictable and well handled by texture-aware reconstruction.
- Lookbooks and campaigns: AI-first too, with a person checking every reflection against the product before delivery.
Building glare cleanup into your catalogue
At catalogue scale, put glare cleanup at the point where images come in. Vendor files, photographer drops, and old catalogue images all benefit from one cleanup step before anything reaches the product page or a marketplace listing.
At Kaptured.AI we do this as part of every catalog and PDP shoot: we clean, retouch and check each image before it is delivered. See how our pricing works for a catalogue refresh.
Related reading
- AI photo cleanup for dust, fingerprints, and clutter
- AI photo enhancer for sharpness, contrast, and white balance after cleanup
- AI jewelry photoshoots by category for jewelry catalogue production
- Glossary: packshot, ghost mannequin photography
Next steps
If you handle glare by hand today, test AI-first removal on a representative sample: 10 images covering your worst-case products. Compare the result with your current Photoshop pass, then weigh the time and cost across your full catalogue.
