RAW is a digital image format that contains unprocessed or minimally processed data captured directly from a digital camera's image sensor. Unlike other common image formats like JPEG, which apply compression and discard some of the original image data, RAW files preserve all of the original data collected by the camera sensor. This allows for significantly more flexibility and control in post-processing, as the photographer has access to the full range of data captured by the camera.
The RAW format is not a single, standardized format but rather a general term that encompasses various proprietary formats developed by camera manufacturers. Each camera maker has its own specific RAW format, such as .CR2 for Canon, .NEF for Nikon, .ARW for Sony, and .DNG for Adobe's Digital Negative format. Despite the differences in file extensions and specific data structures, all RAW formats serve the same purpose of storing uncompressed, minimally processed image data.
One of the primary advantages of shooting in RAW is the increased bit depth compared to JPEG files. While JPEG files are typically limited to 8 bits per color channel (red, green, and blue), RAW files can contain 12, 14, or even 16 bits per channel. This higher bit depth allows for a much broader range of colors and tonal values, providing more latitude for adjustments in post-processing without introducing artifacts or losing detail.
Another benefit of RAW files is the retention of metadata, which includes information about the camera settings used during the capture, such as ISO, shutter speed, aperture, white balance, and more. This metadata is embedded within the RAW file and can be used by post-processing software to optimize image adjustments and maintain a record of the original camera settings.
The flexibility of RAW files is particularly evident when it comes to white balance adjustments. Since RAW files contain the unprocessed color data from the camera sensor, white balance settings can be easily modified in post-processing without significant loss of quality. This is in contrast to JPEG files, where white balance is permanently baked into the image during in-camera processing.
Dynamic range, which refers to the range of luminance values that can be captured by the camera sensor, is another area where RAW files excel. RAW files typically contain a wider dynamic range than JPEG files, allowing for more detail to be preserved in both highlights and shadows. This is particularly useful in high-contrast scenes, where the photographer may want to recover detail in bright or dark areas of the image.
Despite the many advantages of RAW files, there are also some drawbacks to consider. One of the main challenges is the larger file size compared to JPEG files. Since RAW files contain uncompressed data, they require more storage space and can quickly fill up memory cards. Additionally, RAW files require specialized software for viewing and editing, as they cannot be directly displayed by most standard image viewers.
When it comes to editing RAW files, photographers have a wide range of software options available, including Adobe Lightroom, Capture One, and DxO PhotoLab. These programs offer advanced tools for adjusting exposure, color, sharpness, and other image parameters, taking full advantage of the data stored within the RAW files. Many of these software packages also include camera-specific profiles that optimize the rendering of RAW files from particular camera models.
In addition to the proprietary RAW formats used by camera manufacturers, there is also an open-source RAW format called DNG (Digital Negative), developed by Adobe. DNG is designed to provide a standardized, archival format for storing RAW image data, with the goal of ensuring long-term compatibility and reducing the reliance on proprietary formats. Some camera manufacturers have adopted DNG as an optional format, while others continue to use their own proprietary RAW formats.
While RAW files offer significant advantages in terms of image quality and editing flexibility, they may not be necessary or practical for every shooting situation. In cases where speed and simplicity are priorities, such as in sports or event photography, shooting in JPEG can be a more efficient choice. Additionally, some photographers may prefer the look of in-camera JPEG processing, particularly if they have invested time in developing custom camera profiles.
Ultimately, the decision to shoot in RAW or JPEG (or both) depends on the individual photographer's needs, workflow, and personal preferences. For those who prioritize image quality and post-processing flexibility, shooting in RAW can provide a wealth of data to work with and allow for greater creative control. However, photographers should also consider factors such as storage requirements, editing time, and the intended use of the images when deciding on a file format.
As digital imaging technology continues to evolve, it is likely that RAW formats will also advance, offering even greater bit depths, dynamic range, and other improvements. Manufacturers may also develop new compression techniques that reduce file sizes while maintaining the benefits of RAW data. Regardless of future developments, understanding the capabilities and limitations of RAW files is essential for photographers who want to maximize the quality and versatility of their digital images.
File compression reduces redundancy so the same information takes fewer bits. The upper bound on how far you can go is governed by information theory: for lossless compression, the limit is the entropy of the source (see Shannon’s source coding theorem and his original 1948 paper “A Mathematical Theory of Communication”). For lossy compression, the trade-off between rate and quality is captured by rate–distortion theory.
Most compressors have two stages. First, a model predicts or exposes structure in the data. Second, a coder turns those predictions into near-optimal bit patterns. A classic modeling family is Lempel–Ziv: LZ77 (1977) and LZ78 (1978) detect repeated substrings and emit references instead of raw bytes. On the coding side, Huffman coding (see the original paper 1952) assigns shorter codes to more likely symbols. Arithmetic coding and range coding are finer-grained alternatives that squeeze closer to the entropy limit, while modern Asymmetric Numeral Systems (ANS) achieves similar compression with fast table-driven implementations.
DEFLATE (used by gzip, zlib, and ZIP) combines LZ77 with Huffman coding. Its specs are public: DEFLATE RFC 1951, zlib wrapper RFC 1950, and gzip file format RFC 1952. Gzip is framed for streaming and explicitly does not attempt to provide random access. PNG images standardize DEFLATE as their only compression method (with a max 32 KiB window), per the PNG spec “Compression method 0… deflate/inflate… at most 32768 bytes” and W3C/ISO PNG 2nd Edition.
Zstandard (zstd): a newer general-purpose compressor designed for high ratios with very fast decompression. The format is documented in RFC 8878 (also HTML mirror) and the reference spec on GitHub. Like gzip, the basic frame doesn’t aim for random access. One of zstd’s superpowers is dictionaries: small samples from your corpus that dramatically improve compression on many tiny or similar files (see python-zstandard dictionary docs and Nigel Tao’s worked example). Implementations accept both “unstructured” and “structured” dictionaries (discussion).
Brotli: optimized for web content (e.g., WOFF2 fonts, HTTP). It mixes a static dictionary with a DEFLATE-like LZ+entropy core. The spec is RFC 7932, which also notes a sliding window of 2WBITS−16 with WBITS in [10, 24] (1 KiB−16 B up to 16 MiB−16 B) and that it does not attempt random access. Brotli often beats gzip on web text while decoding quickly.
ZIP container: ZIP is a file archive that can store entries with various compression methods (deflate, store, zstd, etc.). The de facto standard is PKWARE’s APPNOTE (see APPNOTE portal, a hosted copy, and LC overviews ZIP File Format (PKWARE) / ZIP 6.3.3).
LZ4 targets raw speed with modest ratios. See its project page (“extremely fast compression”) and frame format. It’s ideal for in-memory caches, telemetry, or hot paths where decompression must be near RAM speed.
XZ / LZMA push for density (great ratios) with relatively slow compression. XZ is a container; the heavy lifting is typically LZMA/LZMA2 (LZ77-like modeling + range coding). See .xz file format, the LZMA spec (Pavlov), and Linux kernel notes on XZ Embedded. XZ usually out-compresses gzip and often competes with high-ratio modern codecs, but with slower encode times.
bzip2 applies the Burrows–Wheeler Transform (BWT), move-to-front, RLE, and Huffman coding. It’s typically smaller than gzip but slower; see the official manual and man pages (Linux).
“Window size” matters. DEFLATE references can only look back 32 KiB (RFC 1951 and PNG’s 32 KiB cap noted here). Brotli’s window ranges from about 1 KiB to 16 MiB (RFC 7932). Zstd tunes window and search depth by level (RFC 8878). Basic gzip/zstd/brotli streams are designed for sequential decoding; the base formats don’t promise random access, though containers (e.g., tar indexes, chunked framing, or format-specific indexes) can layer it on.
The formats above are lossless: you can reconstruct exact bytes. Media codecs are often lossy: they discard imperceptible detail to hit lower bitrates. In images, classic JPEG (DCT, quantization, entropy coding) is standardized in ITU-T T.81 / ISO/IEC 10918-1. In audio, MP3 (MPEG-1 Layer III) and AAC (MPEG-2/4) rely on perceptual models and MDCT transforms (see ISO/IEC 11172-3, ISO/IEC 13818-7, and an MDCT overview here). Lossy and lossless can coexist (e.g., PNG for UI assets; Web codecs for images/video/audio).
Theory: Shannon 1948 · Rate–distortion · Coding: Huffman 1952 · Arithmetic coding · Range coding · ANS. Formats: DEFLATE · zlib · gzip · Zstandard · Brotli · LZ4 frame · XZ format. BWT stack: Burrows–Wheeler (1994) · bzip2 manual. Media: JPEG T.81 · MP3 ISO/IEC 11172-3 · AAC ISO/IEC 13818-7 · MDCT.
Bottom line: choose a compressor that matches your data and constraints, measure on real inputs, and don’t forget the gains from dictionaries and smart framing. With the right pairing, you can get smaller files, faster transfers, and snappier apps — without sacrificing correctness or portability.
File compression is a process that reduces the size of a file or files, typically to save storage space or speed up transmission over a network.
File compression works by identifying and removing redundancy in the data. It uses algorithms to encode the original data in a smaller space.
The two primary types of file compression are lossless and lossy compression. Lossless compression allows the original file to be perfectly restored, while lossy compression enables more significant size reduction at the cost of some loss in data quality.
A popular example of a file compression tool is WinZip, which supports multiple compression formats including ZIP and RAR.
With lossless compression, the quality remains unchanged. However, with lossy compression, there can be a noticeable decrease in quality since it eliminates less-important data to reduce file size more significantly.
Yes, file compression is safe in terms of data integrity, especially with lossless compression. However, like any files, compressed files can be targeted by malware or viruses, so it's always important to have reputable security software in place.
Almost all types of files can be compressed, including text files, images, audio, video, and software files. However, the level of compression achievable can significantly vary between file types.
A ZIP file is a type of file format that uses lossless compression to reduce the size of one or more files. Multiple files in a ZIP file are effectively bundled together into a single file, which also makes sharing easier.
Technically, yes, although the additional size reduction might be minimal or even counterproductive. Compressing an already compressed file might sometimes increase its size due to metadata added by the compression algorithm.
To decompress a file, you typically need a decompression or unzipping tool, like WinZip or 7-Zip. These tools can extract the original files from the compressed format.