# What does OpenEXR say deep images represent and how are deep IDs and subsample alpha meant to interchange between tools?

- id: art_01M5MEN7XW9P96TTBD1YBMHQ4A
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T11 · tags: none
- updated: 2026-10-23T13:19:29.207Z
- url: https://veyrul.com/articles/art_01M5MEN7XW9P96TTBD1YBMHQ4A

Splitting an OpenEXR deep sample recomputes alpha as 1-(1-alpha)^x, which equals un-premultiplying and re-premultiplying colour, with alpha 0 handled as a special case. Deep IDs store 32-bit or paired 64-bit hashes per sample (MurmurHash3 suggested, not required) with a manifest, keeping per-sample colour and alpha so isolated objects keep correct edges; Cryptomatte stores coverage only.

Splitting an OpenEXR deep sample recomputes alpha as 1-(1-alpha)^x, which equals un-premultiplying and re-premultiplying colour, with alpha 0 handled as a special case. Deep IDs store 32-bit or paired 64-bit hashes per sample (MurmurHash3 suggested, not required) with a manifest, keeping per-sample colour and alpha so isolated objects keep correct edges; Cryptomatte stores coverage only.

Curator qualifications: Specifications read 2026-10-22; no images composited.

Limitations: Specifications read 2026-10-22; no images composited.

Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

```json
{
  "citations": [
    {
      "url": "https://github.com/AcademySoftwareFoundation/openexr/blob/dbdc101a3b754ee21f0e70ed28ffec1cba32c78e/website/TheoryDeepPixels.rst",
      "note": "OpenEXR dbdc101a website/TheoryDeepPixels.rst L246, L298-L305; OpenEXR dbdc101a website/DeepIDsSpecification.rst L58-L77, L100-L101, L170-L177"
    },
    {
      "url": "https://github.com/AcademySoftwareFoundation/openexr/blob/dbdc101a3b754ee21f0e70ed28ffec1cba32c78e/website/DeepIDsSpecification.rst",
      "note": "OpenEXR dbdc101a website/TheoryDeepPixels.rst L246, L298-L305; OpenEXR dbdc101a website/DeepIDsSpecification.rst L58-L77, L100-L101, L170-L177"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] Splitting an OpenEXR deep sample recomputes alpha as 1-(1-alpha)^x, which equals un-premultiplying and re-premultiplying colour, with alpha 0 handled as a special case. Deep IDs store 32-bit or paired 64-bit hashes per sample (MurmurHash3 suggested, not required) with a manifest, keeping per-sample colour and alpha so isolated objects keep correct edges; Cryptomatte stores coverage only. · locator: OpenEXR dbdc101a website/TheoryDeepPixels.rst L246, L298-L305; OpenEXR dbdc101a website/DeepIDsSpecification.rst L58-L77, L100-L101, L170-L177 · source: https://github.com/AcademySoftwareFoundation/openexr/blob/dbdc101a3b754ee21f0e70ed28ffec1cba32c78e/website/TheoryDeepPixels.rst

Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=unknown training=unknown · Applies to this original summary only, not to the cited sources.

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