Image MIME Reference
JPEG-AI
JPEG AI Image
image/jaii
VS
PCO B16 Image
image/vnd.pco.b16
PCO-B16
A complete technical comparison of JPEG AI Image and PCO B16 Image — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.
Equal browser support
Feature Support
| Feature | JPEG-AI | PCO-B16 |
|---|---|---|
| Transparency (Alpha) | Yes | ✕ No |
| Animation Support | Yes | ✕ No |
| Progressive Loading | Yes | ✕ No |
| HDR Support | Yes | ✕ No |
| EXIF Metadata | Yes | ✕ No |
| ICC Color Profile | Yes | ✕ No |
JPEG AI Image
image/jaii
Extension
.jaii
Container
ISOBMFF / HEIF
Compression
Lossy (Variational Autoencoder / Neural Network)
Algorithm
Deep Neural Network (Variational Autoencoder with Hyperpriors)
Color Depth
8-bit, 10-bit, 12-bit, 16-bit, Wide-gamut & HDR
Developed by
Joint Photographic Experts Group (ISO/IEC JTC 1 / ITU-T)
Released
2025
Magic Bytes
.. .. .. .. 66 74 79 70 6A 61 69 69 (Size + ftypjaii)
PCO B16 Image
image/vnd.pco.b16
Extension
.b16
Container
PCO B16 Binary Container
Compression
Uncompressed (Raw Sensor Data)
Algorithm
None
Color Depth
16-bit (Monochrome or Bayer Raw Color)
Developed by
PCO AG (Excelitas PCO GmbH)
Released
Early 2000s
Magic Bytes
50 43 4F 2D
Browser Support Comparison
| Browser | JPEG-AI | PCO-B16 |
|---|---|---|
Chrome
|
✕ | ✕ |
Firefox
|
✕ | ✕ |
Safari
|
✕ | ✕ |
Edge
|
✕ | ✕ |
IE (Legacy)
|
✕ | ✕ |
JPEG-AI
JPEG-AI Strengths
- Provides state-of-the-art compression efficiency, dramatically outperforming traditional block-transform codecs like JPEG or HEIC [2.2.2]
- Allows machine vision models to process the raw 'latent tensors' in the compressed stream natively, drastically reducing inference latency by bypassing image reconstruction
- Supports 'multi-branch decoding', enabling a single codestream to be decoded at varying complexity levels depending on the target hardware's power (e.g., mobile NPU vs. cloud GPU)
Limitations
- Lacks native decoding support in current web browsers and legacy operating systems [3.2.1]
- Decoding relies on neural network inference which can be heavily computationally demanding on hardware lacking dedicated AI accelerators (NPUs/GPUs)
- Introduces new vectors for security and forensic analysis, as end-to-end learned structures react differently to adversarial attacks compared to traditional formats
PCO-B16
PCO-B16 Strengths
- Preserves exact, uncompressed 16-bit raw sensor data, which is critically important for accurate scientific measurements, fluorescence microscopy, and photometry
- The simple, linear struct header is highly predictable and easy to parse in custom Python, MATLAB, or C++ scripts for researchers building bespoke pipelines
Limitations
- Generates massive file sizes due to the complete lack of image compression [1.3.1]
- Completely unsupported by standard operating systems, web browsers, and consumer image editing suites
- Strictly tied to the hardware and software ecosystems of a single camera manufacturer
When to choose which format
JPEG-AI
Use JPEG-AI when…
- Machine Vision and AI Workflows
- Cloud Storage Image Optimization
- High-Efficiency Mobile Image Capture
- Visual Surveillance
PCO-B16
Use PCO-B16 when…
- Microscopy and Life Sciences
- High-Speed Camera Recording
- Machine Vision and Industrial Inspection
- Scientific Photometry