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Image MIME Reference
JPEG-AI-Sequence

JPEG AI Image Sequence

image/jais
VS

Sony SRF Raw Image

image/x-sony-srf
Sony-SRF

A complete technical comparison of JPEG AI Image Sequence and Sony SRF Raw Image — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.

Equal browser support

Feature Support

Feature JPEG-AI-Sequence Sony-SRF
Transparency (Alpha) Yes ✕ No
Animation Support Yes ✕ No
Progressive Loading Yes ✕ No
HDR Support Yes Yes
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 →
Sony SRF Raw Image
image/x-sony-srf
Extension
.srf
Container TIFF-based (Proprietary)
Compression Uncompressed
Algorithm
None
Color Depth 12-bit (Per Channel)
Developed by Sony Corporation
Released 2003
Magic Bytes
49 49 2A 00
Full Sony-SRF reference →

Browser Support Comparison

Browser JPEG-AI-Sequence Sony-SRF
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
Sony-SRF

Sony-SRF Strengths

  • Retains perfectly raw, unprocessed sensor data from legacy early-2000s cameras, allowing modern raw processors to extract much better dynamic range and color than the camera's original internal JPEG engine could
  • Utilizes a standard TIFF container structure, ensuring broad compatibility with community-maintained open-source decoding libraries like LibRaw
Limitations
  • Completely obsolete format that has long been abandoned in favor of ARW
  • MIME detection via magic bytes is unreliable due to TIFF header spoofing, requiring deeper EXIF inspection for accurate routing
  • Cannot be natively viewed in web browsers or standard operating system image viewers without specialized decoders

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
Sony-SRF
Use Sony-SRF when…
  • Legacy Sony Cyber-shot Photography
  • Non-destructive Image Post-Processing
  • Early 2000s Raw Imaging Archival

More comparisons

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