DPX Background Remover
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Background removal separates a subject from its surroundings so you can place it on transparency, swap the scene, or composite it into a new design. Under the hood you’re estimating an alpha matte—a per-pixel opacity from 0 to 1—and then alpha-compositing the foreground over something else. This is the math from Porter–Duff and the cause of familiar pitfalls like “fringes” and straight vs. premultiplied alpha. For practical guidance on premultiplication and linear color, see Microsoft’s Win2D notes, Søren Sandmann, and Lomont’s write-up on linear blending.
The main ways people remove backgrounds
1) Chroma key (“green/blue screen”)
If you can control capture, paint the backdrop a solid color (often green) and key that hue away. It’s fast, battle-tested in film and broadcast, and ideal for video. The trade-offs are lighting and wardrobe: colored light spills onto edges (especially hair), so you’ll use despill tools to neutralize contamination. Good primers include Nuke’s docs, Mixing Light, and a hands-on Fusion demo.
2) Interactive segmentation (classic CV)
For single images with messy backgrounds, interactive algorithms need a few user hints—e.g., a loose rectangle or scribbles—and converge to a crisp mask. The canonical method is GrabCut (book chapter), which learns color models for foreground/background and uses graph cuts iteratively to separate them. You’ll see similar ideas in GIMP’s Foreground Select based on SIOX (ImageJ plugin).
3) Image matting (fine-grained alpha)
Matting solves fractional transparency at wispy boundaries (hair, fur, smoke, glass). Classic closed-form matting takes a trimap (definitely-fore/definitely-back/unknown) and solves a linear system for alpha with strong edge fidelity. Modern deep image matting trains neural nets on the Adobe Composition-1K dataset (MMEditing docs), and is evaluated with metrics like SAD, MSE, Gradient, and Connectivity (benchmark explainer).
4) Deep learning cutouts (no trimap)
- U2-Net (salient-object detection) is a strong general “remove background” engine (repo).
- MODNet targets real-time portrait matting (PDF).
- F, B, Alpha (FBA) Matting jointly predicts foreground, background, and alpha to reduce color halos (repo).
- Background Matting V2 assumes a background plate and yields strand-level mattes in real time at up to 4K/30fps (project page, repo).
Related segmentation work is also useful: DeepLabv3+ refines boundaries with an encoder–decoder and atrous convolutions (PDF); Mask R-CNN gives per-instance masks (PDF); and SAM (Segment Anything) is a promptable foundation model that zero-shots masks on unfamiliar images.
What popular tools do
- Photoshop: Remove Background quick action runs “Select Subject → layer mask” under the hood (confirmed here; tutorial).
- GIMP: Foreground Select (SIOX).
- Canva: 1-click Background Remover for images and short video.
- remove.bg: web app + API for automation.
- Apple devices: system-level “Lift Subject” in Photos/Safari/Quick Look (cutouts on iOS).
Workflow tips for cleaner cutouts
- Shoot smart. Good lighting and strong subject–background contrast help every method. With green/blue screens, plan for despill (guide).
- Start broad, refine narrow. Run an automatic selection (Select Subject, U2-Net, SAM), then refine edges with brushes or matting (e.g., closed-form).
- Mind semi-transparency. Glass, veils, motion blur, flyaway hair need true alpha (not just a hard mask). Methods that also recover F/B/α minimize halos.
- Know your alpha. Straight vs. premultiplied produce different edge behavior; export/composite consistently (see overview, Hargreaves).
- Pick the right output. For “no background,” deliver a raster with a clean alpha (e.g., PNG/WebP) or keep layered files with masks if further edits are expected. The key is the quality of the alpha you computed—rooted in Porter–Duff.
Quality & evaluation
Academic work reports SAD, MSE, Gradient, and Connectivity errors on Composition-1K. If you’re picking a model, look for those metrics (metric defs; Background Matting metrics section). For portraits/video, MODNet and Background Matting V2 are strong; for general “salient object” images, U2-Net is a solid baseline; for tough transparency, FBA can be cleaner.
Common edge cases (and fixes)
- Hair & fur: favor matting (trimap or portrait matting like MODNet) and inspect on a checkerboard.
- Fine structures (bike spokes, fishing line): use high-res inputs and a boundary-aware segmenter such as DeepLabv3+ as a pre-step before matting.
- See-through stuff (smoke, glass): you need fractional alpha and often foreground color estimation (FBA).
- Video conferencing: if you can capture a clean plate, Background Matting V2 looks more natural than naive “virtual background” toggles.
Where this shows up in the real world
- E-commerce: marketplaces (e.g., Amazon) often require a pure white main image background; see Product image guide (RGB 255,255,255).
- Design tools: Canva’s Background Remover and Photoshop’s Remove Background streamline quick cutouts.
- On-device convenience: iOS/macOS “Lift Subject” is great for casual sharing.
Why cutouts sometimes look fake (and fixes)
- Color spill: green/blue light wraps onto the subject—use despill controls or targeted color replacement.
- Halo/fringes: usually an alpha-interpretation mismatch (straight vs. premultiplied) or edge pixels contaminated by the old background; convert/interpret correctly (overview, details).
- Wrong blur/grain: paste a razor-sharp subject into a soft background and it pops; match lens blur and grain after compositing (see Porter–Duff basics).
TL;DR playbook
- If you control capture: use chroma key; light evenly; plan despill.
- If it’s a one-off photo: try Photoshop’s Remove Background, Canva’s remover, or remove.bg; refine with brushes/matting for hair.
- If you need production-grade edges: use matting ( closed-form or deep) and check alpha on transparency; mind alpha interpretation.
- For portraits/video: consider MODNet or Background Matting V2; for click-guided segmentation, SAM is a powerful front-end.
What is the DPX format?
SMTPE 268M-2003 (DPX 2.0) image
The Digital Picture Exchange (DPX) format is an image file format specifically designed for the transfer of still frames and sequences between different equipment and applications in the film and television industry. Originating from Kodak's Cineon (.cin) file format, the DPX format was developed to standardize the exchange of film images and their metadata between digital intermediate (DI) systems, visual effects (VFX) applications, and color grading tools. The Society of Motion Picture and Television Engineers (SMPTE) standardized the DPX format under SMPTE 268M, ensuring comprehensive compatibility and broad acceptance in the industry.
DPX files are large, uncompressed bitmapped images that store image data in a straightforward manner, allowing for high-quality, high-resolution pictures necessary for professional film and television production. They are capable of storing image data at various resolutions, aspect ratios, and color depths, which makes them incredibly versatile. Typically, DPX files use a 10-bit log or 16-bit linear color depth to accommodate the high dynamic range required in professional video and film workflows. This capability ensures that DPX files can represent a wide luminance range, from the darkest shadows to the brightest highlights, without data loss.
One of the key features of the DPX format is its support for extensive metadata. This metadata can include information about the film or video source, such as the film's type, production details, camera specifics, and the time code of the frame. Additionally, it can carry color management information, including color primaries, transfer characteristics, and colorimetric data. This wealth of metadata is critical for ensuring that images are accurately processed and reproduced across various devices and applications, maintaining consistency in color grading and effects application throughout the post-production process.
The DPX file header plays a crucial role in storing metadata and guiding applications on how to interpret the image data properly. The header is divided into sections including file information, image information, orientation information, film information, and television information, each containing specific metadata types. For instance, the file information section contains general data like the version number of the DPX format and the file size, while the image information section details the image's resolution, aspect ratio, and color information.
In terms of technical specifics, DPX files can be saved in either big-endian or little-endian byte order, making them adaptable to different computing environments. A distinctive feature of the DPX format is the ability to store multiple images within a single file, facilitating the representation of stereoscopic (3D) content or sequences of images for animation and effects work. This feature underscores the format's design for flexibility in complex production workflows, enabling seamless integration and exchange of content.
The DPX format supports various color models, including RGB, CIE XYZ, and YCbCr, allowing for compatibility with a wide range of input and output devices. For RGB images, each channel (Red, Green, and Blue) is typically stored separately, and there's support for an additional alpha channel for transparency information, crucial for compositing in visual effects. This flexibility in color representation ensures that DPX files can be used in almost any digital imaging process, from initial capture through to final delivery.
Compression is not a core feature of the DPX format, as it aims to preserve the utmost image fidelity and detail for professional use. However, to manage the resulting large file sizes, especially when dealing with high-resolution or multi-image files, applications that use DPX often implement their own file handling and storage solutions. These solutions may include high-capacity, high-speed storage systems and efficient file transfer protocols to handle the substantial data volumes associated with DPX files efficiently.
DPX files are typically used in a linear color space, which means the values stored represent linear light levels. Working in a linear color space allows for more accurate computations and manipulations of light and color, which are essential in achieving photorealistic effects and high-quality image composites. Nonetheless, the support for log color spaces also caters to workflows that rely on film-like response curves, providing versatility in handling different types of source material and aesthetic choices.
Version control and revision handling are crucial in collaborative environments, and while the DPX format itself does not directly support versioning within the file structure, metadata fields in the header can be used to track version information, scene numbers, and take numbers. This approach allows teams to organize, manage, and retrieve specific versions of an image or sequence throughout the production pipeline, promoting efficiency and reducing the likelihood of errors or overwrites.
Beyond its technical specifications, the DPX format's significance lies in its role in bridging the gap between traditional film production and the digital post-production process. By providing a reliable, standardized format for image exchange, DPX facilitates the seamless integration of analog and digital elements within the filmmaking process. This integration is crucial for preserving the artistic intent of filmmakers while leveraging the creative and technical advantages of digital post-production techniques.
The adaptation and use of the DPX format in industry-standard software and hardware underline its importance. Major digital intermediate systems, visual effects software, and color grading tools support the DPX format, enabling a smooth workflow across different stages of production. The ability to handle DPX files is considered a baseline requirement for professional-grade software in the film and television industry, which speaks volumes about the format's pervasive influence.
Despite its strengths, the DPX format faces challenges, particularly related to the large file sizes and the need for substantial storage and bandwidth to manage these files effectively. The emergence of new image formats and codecs that offer high-quality imaging with compression options presents a competitive landscape. However, the DPX format's emphasis on uncompromised image quality, combined with its support for extensive metadata and industry-standard adoption, continues to make it a preferred choice for high-end production workflows.
Looking forward, the DPX format continues to evolve, with updates and revisions aimed at addressing the changing needs of the industry. These updates ensure it remains compatible with newer technologies and workflows while maintaining its core characteristics of high fidelity and flexibility. As the industry moves towards higher resolutions, increased dynamic range, and more complex production techniques, the DPX format's adaptability and support for advanced features will be key to its continued relevance.
In conclusion, the DPX image format stands as a pivotal tool in the professional film and television production landscape. Its design to preserve high image quality, support for extensive metadata, and adaptability across various workflows make it an indispensable asset. The DPX format exemplifies the intersection of artistic vision and technological advancement, facilitating the creation and manipulation of images in a way that respects both the craft of filmmaking and the demands of digital post-production. As the industry evolves, the DPX format's role in maintaining high standards of image fidelity and interoperability across different platforms and processes will undoubtedly continue to be of critical importance.
Supported formats
AAI.aai
AAI Dune image
AI.ai
Adobe Illustrator CS2
AVIF.avif
AV1 Image File Format
BAYER.bayer
Raw Bayer Image
BMP.bmp
Microsoft Windows bitmap image
CIN.cin
Cineon Image File
CLIP.clip
Image Clip Mask
CMYK.cmyk
Raw cyan, magenta, yellow, and black samples
CUR.cur
Microsoft icon
DCX.dcx
ZSoft IBM PC multi-page Paintbrush
DDS.dds
Microsoft DirectDraw Surface
DPX.dpx
SMTPE 268M-2003 (DPX 2.0) image
DXT1.dxt1
Microsoft DirectDraw Surface
EPDF.epdf
Encapsulated Portable Document Format
EPI.epi
Adobe Encapsulated PostScript Interchange format
EPS.eps
Adobe Encapsulated PostScript
EPSF.epsf
Adobe Encapsulated PostScript
EPSI.epsi
Adobe Encapsulated PostScript Interchange format
EPT.ept
Encapsulated PostScript with TIFF preview
EPT2.ept2
Encapsulated PostScript Level II with TIFF preview
EXR.exr
High dynamic-range (HDR) image
FF.ff
Farbfeld
FITS.fits
Flexible Image Transport System
GIF.gif
CompuServe graphics interchange format
HDR.hdr
High Dynamic Range image
HEIC.heic
High Efficiency Image Container
HRZ.hrz
Slow Scan TeleVision
ICO.ico
Microsoft icon
ICON.icon
Microsoft icon
J2C.j2c
JPEG-2000 codestream
J2K.j2k
JPEG-2000 codestream
JNG.jng
JPEG Network Graphics
JP2.jp2
JPEG-2000 File Format Syntax
JPE.jpe
Joint Photographic Experts Group JFIF format
JPEG.jpeg
Joint Photographic Experts Group JFIF format
JPG.jpg
Joint Photographic Experts Group JFIF format
JPM.jpm
JPEG-2000 File Format Syntax
JPS.jps
Joint Photographic Experts Group JPS format
JPT.jpt
JPEG-2000 File Format Syntax
JXL.jxl
JPEG XL image
MAP.map
Multi-resolution Seamless Image Database (MrSID)
MAT.mat
MATLAB level 5 image format
PAL.pal
Palm pixmap
PALM.palm
Palm pixmap
PAM.pam
Common 2-dimensional bitmap format
PBM.pbm
Portable bitmap format (black and white)
PCD.pcd
Photo CD
PCT.pct
Apple Macintosh QuickDraw/PICT
PCX.pcx
ZSoft IBM PC Paintbrush
PDB.pdb
Palm Database ImageViewer Format
PDF.pdf
Portable Document Format
PDFA.pdfa
Portable Document Archive Format
PFM.pfm
Portable float format
PGM.pgm
Portable graymap format (gray scale)
PGX.pgx
JPEG 2000 uncompressed format
PICT.pict
Apple Macintosh QuickDraw/PICT
PJPEG.pjpeg
Joint Photographic Experts Group JFIF format
PNG.png
Portable Network Graphics
PNG00.png00
PNG inheriting bit-depth, color-type from original image
PNG24.png24
Opaque or binary transparent 24-bit RGB (zlib 1.2.11)
PNG32.png32
Opaque or binary transparent 32-bit RGBA
PNG48.png48
Opaque or binary transparent 48-bit RGB
PNG64.png64
Opaque or binary transparent 64-bit RGBA
PNG8.png8
Opaque or binary transparent 8-bit indexed
PNM.pnm
Portable anymap
PPM.ppm
Portable pixmap format (color)
PS.ps
Adobe PostScript file
PSB.psb
Adobe Large Document Format
PSD.psd
Adobe Photoshop bitmap
RGB.rgb
Raw red, green, and blue samples
RGBA.rgba
Raw red, green, blue, and alpha samples
RGBO.rgbo
Raw red, green, blue, and opacity samples
SIX.six
DEC SIXEL Graphics Format
SUN.sun
Sun Rasterfile
SVG.svg
Scalable Vector Graphics
TIFF.tiff
Tagged Image File Format
VDA.vda
Truevision Targa image
VIPS.vips
VIPS image
WBMP.wbmp
Wireless Bitmap (level 0) image
WEBP.webp
WebP Image Format
YUV.yuv
CCIR 601 4:1:1 or 4:2:2
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