computer science

OpenEXR

OpenEXR is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand OpenEXR rather than just read about it. In short: OpenEXR is a high-dynamic range, multi-channel raster file format, released as an open standard along with a set of software tools created by Industrial Light & Magic (ILM), under a free software license similar to the BSD license. It is notable for supporting multiple channels of potentially different pixel sizes, including 32-bit unsigned integer, 32-bit and 16-bit floating point values, as well as various compres…

Key takeaways

OpenEXR belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect OpenEXR to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of OpenEXR from memory before moving on to harder problems.

Reference excerpt

OpenEXR is a high-dynamic range, multi-channel raster file format, released as an open standard along with a set of software tools created by Industrial Light & Magic (ILM), under a free software license similar to the BSD license. It is notable for supporting multiple channels of potentially different pixel sizes, including 32-bit unsigned integer, 32-bit and 16-bit floating point values, as well as various compression techniques which include lossless and lossy compression algorithms. It also has arbitrary channels and encodes multiple points of view such as left- and right-camera images.

Overview A full technical introduction of the format is available on the OpenEXR website. OpenEXR, or EXR for short, is a deep raster format developed by ILM and broadly used in the computer-graphics industry, both visual effects and animation. OpenEXR's multi-resolution and arbitrary channel format makes it appealing for compositing, as it alleviates several painful elements of the process. Since it can store arbitrary channels—specular, diffuse, alpha, RGB, normals, and various other types—in one file, it takes away the need to store this information in separate files. The multi-channel concept also reduces the necessity to "bake" in the aforementioned data to the final image. If a compositor is not happy with the current level of specularity, they can adjust that specific channel. OpenEXR's API makes tools development a relative ease for developers. Since there are almost never two identical production pipelines, custom tools always need to be developed to address problems (e.g. image-manipulation issue). OpenEXR's library allows quick and easy access to the image's attributes such as tiles and channels. The OpenEXR library is developed in C++ and is available in source format as well as compiled format for Microsoft Windows, macOS and Linux. Python bindings for the library are also available for version 2.x.

History OpenEXR was created by ILM in 1999 and released to the public in 2003 along with an open source software library. It soon received wide adoption by software used in computer graphics, particularly for film and television production. The format has been updated several times, adding support for tiles, mipmaps, new compression methods, and other features. In 2007, OpenEXR was honored with an Academy Award for Technical Achievement. OpenEXR 2.0 was released in April 2013, extending the format with support for deep image buffers and multiple images embedded in a single file. Version 2.2, released August 2014, added the lossy DWA compression format.

Distribution The OpenEXR software distribution includes:

libraries Half, a C++ class for manipulating half values as if they were a built-in C++ data type exrdisplay, a sample application for viewing OpenEXR images on a display at various exposure settings

Libraries IlmImf = library made by Industrial Light & Magic (Ilm) for low-level operations on the files with OpenEXR image format (Imf) libIlmImf on linux IlmImf.dll on windows IlmImfUtil Imath

Color depth OpenEXR has support for color depth using:

16-bit floating-point (half) 32-bit floating-point 32-bit unsigned integer

Compression methods There are three general types of lossless compression built into OpenEXR, with two different methods of Zip compressing. For most images without a lot of grain, the two Zip compression methods seem to work best, while the PIZ compression algorithm is better suited to grainy images. The following options are available:

None Disables all compression. Run Length Encoding (RLE) This is a basic form of compression that is comparable to that used by standard Targa files. Zip (per scanline) deflate compression with zlib wrapper applied to individual scanlines (not based on the ZIP file format despite its name). Zip (16 scanline blocks) deflate compression applied to blocks of 16 scanlines at time. This tends to be the most effective style of compression to use with rendered images that do not have film grain applied. PIZ (wavelet compression) This lossless method uses a new combined wavelet / Huffman compression. This form of compression is quite effective when dealing with grainy images, and will often surpass any of the other options under grainy conditions. PXR24 (24-bit data conversion then deflate compression) This form of compression from Pixar Animation Studios converts 32-bit floats to 24 bits then uses deflate compression. It is lossless for half and 32-bit integer data and slightly lossy for 32-bit float data. B44 This form of compression is lossy for half data and stores 32-bit data uncompressed. It maintains a fixed compression size of either 2.28:1 or 4.57:1 and is designed for realtime playback. B44 compresses uniformly regardless of image content. B44A An extension to B44 where areas of flat color are further compressed, such as alpha channels. DWAA JPEG-like lossy compression format contributed by DreamWorks Animation. Compresses 32 scanlines together. DWAB Same as DWAA, but compresses blocks of 256 scanlines.

Credits From OpenEXR.org's Technical Introduction:

The ILM OpenEXR file format was designed and implemented by Florian Kainz, Wojciech Jarosz, and Rod Bogart. The PIZ compression scheme is based on an algorithm by Christian Rouet. Josh Pines helped extend the PIZ algorithm for 16-bit and found optimizations for the float-to-half conversions. Drew Hess packaged and adapted ILM's internal source code for public release and maintains the OpenEXR software distribution. The PXR24 compression method is based on an algorithm written by Loren Carpenter at Pixar Animation Studios.

Worked examples

Example 1 — a first encounter with OpenEXR

Start with the simplest possible case. Write down what OpenEXR claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to OpenEXR before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about OpenEXR ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of OpenEXR

In research: OpenEXR appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses OpenEXR in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: OpenEXR is common in secondary-school and first-year university syllabi. It links to neighbouring topics Free graphics software, High dynamic range, High dynamic range file formats, so understanding it makes those chapters shorter.
In everyday life: Look for OpenEXR outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study OpenEXR in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what OpenEXR means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain OpenEXR out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is OpenEXR in simple terms?

Why does OpenEXR matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study OpenEXR?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on OpenEXR.