Image MIME Reference
JPEG-AI-Sequence
JPEG AI Image Sequence
image/jais
VS
Minolta Raw Image
image/x-minolta-mrw
Minolta-MRW
A complete technical comparison of JPEG AI Image Sequence and Minolta 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 | Minolta-MRW |
|---|---|---|
| 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)
Minolta Raw Image
image/x-minolta-mrw
Extension
.mrw
Container
Proprietary MRW Container
Compression
Uncompressed / Proprietary Lossless
Algorithm
NoneProprietary Lossless
Color Depth
12-bit (Per Channel)
Developed by
Minolta (later Konica Minolta)
Released
2001
Magic Bytes
00 4D 52 4D
Browser Support Comparison
| Browser | JPEG-AI-Sequence | Minolta-MRW |
|---|---|---|
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✕ | ✕ |
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✕ | ✕ |
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✕ | ✕ |
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✕ | ✕ |
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✕ | ✕ |
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
Minolta-MRW
Minolta-MRW Strengths
- Retains full, unadulterated sensor data from early CCD digital cameras, allowing modern demosaicing algorithms to extract far superior image quality than what was possible when the cameras were released
- Possesses a very distinct, unambiguous magic header (\x00MRM), making programmatic identification completely foolproof
Limitations
- Completely obsolete proprietary format that has not seen a new camera release since 2006
- Cannot be natively viewed in web browsers or standard operating system image viewers without specialized decoders
- Relies entirely on open-source reverse engineering (like LibRaw) for continued modern software compatibility
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
Minolta-MRW
Use Minolta-MRW when…
- Vintage Digital Photography (Konica Minolta DiMAGE / Maxxum)
- Raw Imaging Archival
- Historical Camera Sensor Research