9to5Mac58%
Apple overhauls RAW photo processing with iOS 27, showcases impressive results 48%
By Marcus Mendes29%
7/6/2026, 10:52:54 PM
BS Summary: This article contains 16 faulty reasoning types, including Anecdotal, Confirmation Bias, and Ambiguity (Equivocation), with Attempt to Sell a Product or Service as the most egregious example at 18.3% saturation with 91 hits. Analysis detected 533 faulty-reasoning hits from 498 analyzed words, generating a BS Score of 49.1% and a BS Rank of 48% (11,465 of 21,887 articles). This article is better (less manipulative) than 52.40% of the article peer group.
With iOS 27 and its companion systems, Apple is introducing a new version of its system-level RAW image processing engine.
It uses machine learning to greatly improve detail and reduce noise, including when reprocessing older RAW photos.
Here are the details.
## iOS 27 to include RAW 9
If you’re not familiar with RAW, it is basically an image format that preserves the data captured directly by a camera’s sensor, giving photographers greater flexibility when editing elements such as exposure, color, and white balance.
Apple has its own system-level pipeline for processing RAW files from third-party cameras, exposed to apps through Core Image.
It currently includes support and camera-specific calibrations for nearly 800 camera models, with the full and regularly updated compatibility list available here.
Over the years, Apple has updated its RAW processing algorithm eight times, improving how it handles sensor data, demosaicing, denoising, and adjustments such as white balance, exposure, color, and tone.
With iOS 27, macOS 27, iPadOS 27 and beyond, Apple is introducing RAW 9, which the company says is “its biggest update yet.”
Here’s David Hayward, Core Image Engineer at Apple, on the WWDC26 session Enhance RAW image processing with Core Image:
> [RAW 9] dramatically improves the rendering of RAW files.
It is built atop a tiled CoreML model, that combines demosaic with denoise for best quality.
And the model is run on device using the Apple Neural Engine cores, for optimal performance.
In the session, Hayward shows several examples of RAW 9 in action, comparing the results with RAW 8 and, occasionally, the original, unprocessed sensor data:
This is a zoomed-in crop of a low noise image using RAW 8.
This Sony Alpha 7 II image of a vintage dial indicator actually looks quite good.
However, when you explore that same image under RAW 9, the image is sharper, clearer, and the fine text is easier to read.
This last example is a crop of a photo of embroidery yarn, shot with a Fujifilm X-T5 at ISO 12,800.
This camera has a non-traditional sensor pattern, which is challenging to demosaic.
In the RAW 8 results, there are some color artifacts and loss of detail in the yarn.
But if you observe the same image under RAW 9, the results are discernibly better.
The small text is more legible, and the texture in the yarn much clearer.
For developers, the session goes into detail on how to enable RAW 9, optimize performance for editing and exporting, and much more.
To learn more about RAW 9 and the other Core Image improvements coming with iOS 27, watch the full session here.
#### Worth checking out on Amazon
* Geoffrey Cain – ‘Steve Jobs in Exile’
* David Pogue – ’Apple: The First 50 Years’
* MacBook Neo
* Logitech MX Master 4
* **AirPods Pro 3**
* AirTag (2nd Generation) – 4 Pack
* Apple Watch Series 11
* Wireless CarPlay adapter
Speakers
1speaker2.0%attributed speech488writer words
Voice mapSelect a segment to jump to its words
Selected voice
100%flagged-word coverageDavid Hayward
10 attributed words100% of attributed speech78% writer coverage
Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.
Loading…
Loading…
Loading…
Loading…
Analysis
Hover over highlighted words in the article to view the associated bias or fallacy analysis.