The Pros and Cons of JPEG 2000 and Other Common Image Formats

In case you wondered if JPEG 2000 is still in use, the answer is a resounding yes. A recent Cloudinary post sheds light on JPEG 2000’s format’s usability and the reasons why it’s not as widely adopted as other formats, such as JPEG, PNG, and GIF. This article elaborates in depth the pros and cons of JPEG 2000 in relation to seven common image formats.

JPEG 2000 is an image-encoding system created in 2000 as a single architecture by the Joint Photographic Experts Group to replace JPEG. Incorporated were state-of-the-art compression techniques based on a discrete transformation of wavelengths, enabling a lossless reduction in file size.

Besides being slated for many types of still images—bilevel, gray level, color, multicomponent—with various characteristics, JPEG 2000 also unifies imaging models, such as those for real-time transmissions, image-library archival, limited buffers, and client-server structures. Image compression usually occurs in digital cameras, scanners, frame grabbers, medical mechanisms, satellite systems, and photo-editing programs.

JPEG 2000 performs the following tasks:

• Supports progressive decoding, an efficient code stream that displays a lower-quality version of an image during download. The quality progressively improves as more data bits arrive.
• Delivers both lossless (bit-preserving) and lossy compression within a code stream. As a comparison, JPEG compresses only lossily.
• Preserves the transparency in images.
• Enables the handling of color-space information, metadata, and interactivity in networked applications through the .jp2 and .jpx file formats. As specified in the standard document RFC 3745, the MIME types for JPEG 2000 are image/jp2, video/mj2, image/jpx, and image/jpm.
• Affords higher ratios for lossy compression. As pointed out in a previous post, case studies have revealed that JPEG 2000 can compress images more effectively than JPEG by 20-200 percent. Typically, the peak signal-to-noise ratio or mean square in the root serves as a yardstick for measuring the efficiency of lossy compression.

Ultimately, JPEG 2000 delivers higher quality than JPEG for images of the same size.

Similar to the TIFF image format, JPEG 2000 offers the following benefits:

• The capability of showing bilevel, gray-scale, palette-color, and full-color data in several color spaces.
• No limit for the amount of private or special-purpose information in the metadata.
• Extensibility and seamless evolvement as needs arise for new features.
• A choice of compression schemes with time-space tradeoffs for application developers.
• The capability of handling large images, i.e., those that are greater than 64k x 64k pixels, also natural and computer-generated imagery, without tiling.
• Low bit-rate compression down to below 0.25 bits per pixel for high resolution, gray-scale images.

Additionally, JPEG 2000 offers the following advantages for the production process of video broadcasts:

• An intraframe compression scheme that encodes each frame independently and that can cut video signals anywhere without repercussion—a significant plus for content-editing apps.
• Bit errors, which create less visual artifacts than the standards set by the Moving Picture Experts Group (MPEG).
• Ultra low latency, which is key for live TV content.
• Scalability for both resolution and quality.
• Robust pixel shifts, which retain the same quality improvement in successive compression and decompression processes over the original material.

As awesome as JPEG 2000 is, the undesirable effects of adopting it are nontrivial, hence the format’s limited use and support.

• JPEG 2000 works in only certain browsers.
• JPEG 2000 is not backward compatible. To also leverage the original JPEG format, developers and other digital professionals who adopt JPEG 2000 must code in a new standard.
• Encoding JPEG 2000 files, which involves modifying the CPU and adding code, is resource intensive, requiring much more memory for processing. Given the high capacity of modern machines, that issue likely no longer exists. However, when JPEG 2000 first debuted in 2000, its memory requirement posed a significant concern.
• Websites and camera manufacturers delayed acceptance of JPEG 2000 until it was widely adopted.
• JPEG 2000’s encoding process is slower and more complicated than JPEG’s.
• JPEG 2000 is much less content adaptive than JPEG, and choosing an ultralow target bitrate would mess up an image. Depending on the image content, you would need to manually adjust the bitrate.

Nonetheless, despite its lack of popularity in photography, JPEG 2000 is widely in use in the medical and wireless multimedia arenas. Most diagnostic imagery, such as MRI, CT scans, and X-rays, are encoded as JPEG 2000. Besides, because JPEG 2000 fully meets the data-compression requirements for digital cinema, e.g., high dynamic range, color spaces, high image resolutions, and lossless compression, JPEG 2000 is the format of choice for digital-cinema operations.

The table below shows the pros and cons of the seven most common image formats. Notably, you’ll see at a glance how the three JPEG formats are stacked against one another: JPEG 2000 versus JPEG and JPEG XR.

JPEG 2000 trumps JPEG in many ways. In my opinion, if universal browser support is not a must for your project, JPEG 2000 is your go-to format.

I hope that giant enterprises like Sony and Panasonic as well as developers worldwide will accelerate their adoption of JPEG 2000. Subsequently, browser engines and software developers will be incentivized to jump on the JPEG 2000 bandwagon, resulting in a big step forward for the image-format sphere.

• Image Formats: Getting it Right
• Progressive JPEGs and green Martians
• Animated WebP: How to Convert Animated GIF to WebP and Save Up to 90% Bandwidth
• JPEG Image Optimization Without Compromising Quality With JPEGmini and Cloudinary
• Why JPEG Is Like a Photocopier
• Check for WebP Browser Support to Dynamically Deliver Images
• Adopting the WebP Image Format for Android on Websites Or Native Apps
• Optimizing Animated GIFs With Lossy Compression
• Vue.js Tutorial: Image Optimization for Web Apps