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Image MIME Reference
JPEG-AI-Sequence

JPEG AI Image Sequence

image/jais
VS

JPEG 2000 Compound Image File Format

image/jpm
JPM

A complete technical comparison of JPEG AI Image Sequence and JPEG 2000 Compound Image File Format — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.

Equal browser support

Feature Support

Feature JPEG-AI-Sequence JPM
Transparency (Alpha) Yes Yes
Animation Support Yes ✕ No
Progressive Loading Yes Yes
HDR Support Yes ✕ No
EXIF Metadata Yes Yes
ICC Color Profile Yes Yes
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 →
JPEG 2000 Compound Image File Format
image/jpm
Extension
.jpm.jpgm
Container ISOBMFF / JPM (ISO/IEC 15444-6)
Compression Lossy / Lossless / Mixed Raster Content (MRC)
Algorithm
JPEG 2000JBIG2JPEGMMR
Color Depth 1-bit (Text/Masks), 8-bit, 16-bit, 24-bit
Developed by Joint Photographic Experts Group (JPEG)
Released 2003
Magic Bytes
00 00 00 0C 6A 50 20 20 0D 0A 87 0A ... 66 74 79 70 6A 70 6D 20
Full JPM reference →

Browser Support Comparison

Browser JPEG-AI-Sequence JPM
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
JPM

JPM Strengths

  • Highly optimized for scanned documents, drastically reducing file sizes without sacrificing the readability of text or the quality of embedded photos
  • Supports multi-page documents within a single file
  • Object-based architecture allows for complex layout representation and independent extraction of elements
Limitations
  • Failed to achieve widespread adoption, largely being overshadowed by PDF/A and DjVu
  • Zero native web browser compatibility
  • Requires complex, specialized software to properly encode and decode the multi-layered MRC structure

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
JPM
Use JPM when…
  • Scanned Document Archiving
  • Mixed Raster Content (MRC) Imaging
  • Digital Libraries

More comparisons

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