The typical use case for this high speed Node.js module is to convert large images in common formats to smaller, web-friendly JPEG, PNG and WebP images of varying dimensions.

Resizing an image is typically 4x-5x faster than using the quickest ImageMagick and GraphicsMagick settings.

Colour spaces, embedded ICC profiles and alpha transparency channels are all handled correctly. Lanczos resampling ensures quality is not sacrificed for speed.

As well as image resizing, operations such as rotation, extraction, compositing and gamma correction are available.

OS X, Windows (x64), Linux (x64, ARM) systems do not require the installation of any external runtime dependencies.

Test Coverage


This module supports reading JPEG, PNG, WebP, TIFF, GIF and SVG images.

Output images can be in JPEG, PNG and WebP formats as well as uncompressed raw pixel data.

Streams, Buffer objects and the filesystem can be used for input and output.

A single input Stream can be split into multiple processing pipelines and output Streams.

Deep Zoom image pyramids can be generated, suitable for use with "slippy map" tile viewers like OpenSeadragon and Leaflet.


This module is powered by the blazingly fast libvips image processing library, originally created in 1989 at Birkbeck College and currently maintained by John Cupitt.

Only small regions of uncompressed image data are held in memory and processed at a time, taking full advantage of multiple CPU cores and L1/L2/L3 cache.

Everything remains non-blocking thanks to libuv, no child processes are spawned and Promises/A+ are supported.


Huffman tables are optimised when generating JPEG output images without having to use separate command line tools like jpegoptim and jpegtran.

PNG filtering can be disabled, which for diagrams and line art often produces the same result as pngcrush.


A guide for contributors covers reporting bugs, requesting features and submitting code changes.


This module would never have been possible without the help and code contributions of the following people:

Thank you!


Copyright 2013, 2014, 2015, 2016 Lovell Fuller and contributors.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.