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Image MIME Reference
JPEG-AI-Sequence

JPEG AI Image Sequence

image/jais
VS

PCO B16 Image

image/vnd.pco.b16
PCO-B16

A complete technical comparison of JPEG AI Image Sequence 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-Sequence 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 Sequence
image/jais
Extension
.jais
Container ISOBMFF / HEIF Image Sequence
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 73 (Size + ftypjais)
Full JPEG-AI-Sequence reference →
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
Full PCO-B16 reference →

Browser Support Comparison

Browser JPEG-AI-Sequence PCO-B16
Chrome Chrome
✕ ✕
Firefox Firefox
✕ ✕
Safari Safari
✕ ✕
Edge Edge
✕ ✕
IE IE (Legacy)
✕ ✕
JPEG-AI-Sequence

JPEG-AI-Sequence Strengths

  • Extends the state-of-the-art compression efficiency of JPEG AI to multi-frame image sequences and short animations
  • Allows machine vision algorithms to process temporal sequences (like surveillance bursts) directly in the compressed latent domain, saving immense computational power
  • Utilizes the robust, industry-standard ISOBMFF container for metadata, timing, and multi-track encapsulation
Limitations
  • Lacks native decoding support in current web browsers, operating systems, and video players
  • Decoding neural-network-compressed sequences requires significant compute overhead on hardware lacking dedicated AI accelerators (NPUs/GPUs)
  • Adoption is hindered by competition with established sequence formats like AVIF, HEVC (HEICS), and modern video codecs
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-Sequence
Use JPEG-AI-Sequence when…
  • Machine Vision and AI Video/Burst Workflows
  • Cloud Storage Animation Optimization
  • Focal Stacks and Medical Volumetric Slices
  • Visual Surveillance Sequences
PCO-B16
Use PCO-B16 when…
  • Microscopy and Life Sciences
  • High-Speed Camera Recording
  • Machine Vision and Industrial Inspection
  • Scientific Photometry

More comparisons

JPEG-AI-Sequence vs ACES → PCO-B16 vs ACES → JPEG-AI-Sequence vs APNG → PCO-B16 vs APNG → JPEG-AI-Sequence vs AVCI → PCO-B16 vs AVCI → JPEG-AI-Sequence vs AVCS → PCO-B16 vs AVCS → JPEG-AI-Sequence vs AVIF → PCO-B16 vs AVIF → All comparisons →
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