# What do the OpenEXR deep-pixel document and the Theory of Deep Samples derivation say about splitting, merging and tidying overlapping volume samples, and what assumptions do the formulas rest on?

- id: art_01M5MRMZYY86R2HH6PRE60CG0C
- 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, T12 · tags: none
- updated: 2026-10-23T16:14:06.797Z
- url: https://veyrul.com/articles/art_01M5MRMZYY86R2HH6PRE60CG0C

OpenEXR makes a deep pixel tidy by splitting partially overlapping samples, merging coincident ones and sorting by depth, and flattens by compositing tidy samples front to back; point samples are never merged with volume samples. The maths assumes each sample has constant optical density and colour (split alpha 1-(1-a)^x, merged alpha by the screen equation), so non-uniform media fall outside it.

OpenEXR makes a deep pixel tidy by splitting partially overlapping samples, merging coincident ones and sorting by depth, and flattens by compositing tidy samples front to back; point samples are never merged with volume samples. The maths assumes each sample has constant optical density and colour (split alpha 1-(1-a)^x, merged alpha by the screen equation), so non-uniform media fall outside it.

Curator qualifications: Zero-fetch review 2026-10-22 against held readbacks; nothing composited.

Limitations: Zero-fetch review 2026-10-22 against held readbacks; nothing 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/69b2604fc76e370615438bdc8d2cd95b9349c12e/website/InterpretingDeepPixels.rst",
      "note": "OpenEXR 69b2604f website/InterpretingDeepPixels.rst L503-L575; website/TheoryDeepPixels.rst L101-L105, L129, L243, L365-L370"
    },
    {
      "url": "https://github.com/AcademySoftwareFoundation/openexr/blob/69b2604fc76e370615438bdc8d2cd95b9349c12e/website/TheoryDeepPixels.rst",
      "note": "OpenEXR 69b2604f website/InterpretingDeepPixels.rst L503-L575; website/TheoryDeepPixels.rst L101-L105, L129, L243, L365-L370"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] OpenEXR makes a deep pixel tidy by splitting partially overlapping samples, merging coincident ones and sorting by depth, and flattens by compositing tidy samples front to back; point samples are never merged with volume samples. The maths assumes each sample has constant optical density and colour (split alpha 1-(1-a)^x, merged alpha by the screen equation), so non-uniform media fall outside it. · locator: OpenEXR 69b2604f website/InterpretingDeepPixels.rst L503-L575; website/TheoryDeepPixels.rst L101-L105, L129, L243, L365-L370 · source: https://github.com/AcademySoftwareFoundation/openexr/blob/69b2604fc76e370615438bdc8d2cd95b9349c12e/website/InterpretingDeepPixels.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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