Free webp to jpg
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Image MIME Reference
HEJ2K

JPEG 2000 Image (HEIF Container)

image/hej2k
VS

JPEG AI Image Sequence

image/jais
JPEG-AI-Sequence

A complete technical comparison of JPEG 2000 Image (HEIF Container) and JPEG AI Image Sequence — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.

Equal browser support

Feature Support

Feature HEJ2K JPEG-AI-Sequence
Transparency (Alpha) Yes Yes
Animation Support ✕ No Yes
Progressive Loading Yes Yes
HDR Support Yes Yes
EXIF Metadata Yes Yes
ICC Color Profile Yes Yes
JPEG 2000 Image (HEIF Container)
image/hej2k
Extension
.hej2
Container HEIF / ISOBMFF (ISO/IEC 15444-16)
Compression Lossy / Lossless
Algorithm
JPEG 2000HTJ2K
Color Depth 8-bit, 10-bit, 12-bit, 16-bit
Developed by ISO/IEC JTC 1 / ITU-T
Released 2019
Magic Bytes
XX XX XX XX 66 74 79 70 6A 32 6B 69
Full HEJ2K reference →
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 →

Browser Support Comparison

Browser HEJ2K JPEG-AI-Sequence
Chrome Chrome
✕ ✕
Firefox Firefox
✕ ✕
Safari Safari
✕ ✕
Edge Edge
✕ ✕
IE IE (Legacy)
✕ ✕
HEJ2K

HEJ2K Strengths

  • Brings the extensive capabilities of the HEIF container (like EXIF/XMP, thumbnails, and depth maps) to JPEG 2000
  • Supports mathematically lossless compression via wavelet transformation
  • High scalability and progressive decoding out of the box
Limitations
  • Extremely limited software support outside of niche industries
  • Zero native compatibility with web browsers
  • High computational complexity compared to simpler formats like JPEG or PNG
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

When to choose which format

HEJ2K
Use HEJ2K when…
  • Medical Imaging
  • Geospatial Data
  • Scientific Archiving
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

More comparisons

HEJ2K vs ACES → JPEG-AI-Sequence vs ACES → HEJ2K vs APNG → JPEG-AI-Sequence vs APNG → HEJ2K vs AVCI → JPEG-AI-Sequence vs AVCI → HEJ2K vs AVCS → JPEG-AI-Sequence vs AVCS → HEJ2K vs AVIF → JPEG-AI-Sequence vs AVIF → All comparisons →
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