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gainmap-js

A Javascript (TypeScript) Encoder/Decoder Implementation of Adobe's Gain Map Technology for storing HDR Images using an SDR Image + a "Gain map"

⚠️ This library is primarly intended for encoding and decoding gain map images for the three.js 3D Library

It can be used for general encode/decode of gain maps but it depends on the three.js library which, in itself, is quite heavy if you only use it to encode/decode gainmaps.

Installing

$ npm install @monogrid/gainmap-js threejs

What is a Gain map?

See here for a detailed explanation, here are some relevant parts:

A gain map is a single file with a second pseudo-image embedded in it to create an optimized result for a specific monitor. It can be used to generate the HDR version (which looks dramatically better where supported), the SDR version (without tone mapping to ensures great quality), or anything in between (to better support less capable HDR displays).

Gain maps are not a new type of file, but rather a technology which can be embedded into a variety of image formats. There are reference specs already for the JPG, AVIF, JXL, and HEIF file formats. JPG is especially notable as it could not properly support HDR without gain maps and it offers a very useful bridge to the future (i.e. highly compatible with today’s software).

A gain map includes:

  • A base (default) image. This can be an SDR or an HDR image (JPG gain maps are always encoded with SDR as the base). If the browser or viewing software does not understand gain maps, it will just the treat file as if it were just the base image.
  • The gain map. This is a secondary “image” embedded in the file. It is not a real image, but rather contains data to convert each pixel from the base image into the other (SDR or HDR) version of the image.
  • Gain map metadata. This tells the browser how the gain map is encoded as well as critical information to optimize rendering on any display.

API

Refer to the WIKI for detailed documentation about the API.

Examples

Decoding

The main use case of this library is to decode a JPEG file that contains gain map data and use it instead of a traditional .exr or .hdr image.

import { decode } from '@monogrid/gainmap-js'
import { decodeJPEGMetadata } from '@monogrid/gainmap-js/libultrahdr'
import {
  Mesh,
  MeshBasicMaterial,
  PerspectiveCamera,
  PlaneGeometry,
  Scene,
  WebGLRenderer
} from 'three'

const renderer = new WebGLRenderer()

// fetch a JPEG image containing a gainmap as ArrayBuffer
const gainmap = await (await fetch('gainmap.jpeg')).arrayBuffer()

// extract data from the JPEG
const { sdr, gainMap, parsedMetadata } = await decodeJPEGMetadata(new Uint8Array(gainmap))

// restore the HDR texture
const result = await decode({
  sdr,
  gainMap,
  // this allows to use `result.renderTarget.texture` directly
  renderer,
  // this will restore the full HDR range
  maxDisplayBoost: Math.pow(2, parsedMetadata.hdrCapacityMax),
  ...parsedMetadata
})

const scene = new Scene()
// `result` can be used to populate a Texture
const mesh = new Mesh(
  new PlaneGeometry(),
  new MeshBasicMaterial({ map: result.renderTarget.texture })
)
scene.add(mesh)
renderer.render(scene, new PerspectiveCamera())

Encoding

Encoding a Gain map starting from an EXR file.

This is generally not useful in a three.js site but this library exposes methods that allow to encode an .exr or hdr file into a jpeg with an embedded gain map.

import { compress, encode, findTextureMinMax } from '@monogrid/gainmap-js'
import { encodeJPEGMetadata } from '@monogrid/gainmap-js/libultrahdr'
import { EXRLoader } from 'three/examples/jsm/loaders/EXRLoader.js'

// load an HDR file
const loader = new EXRLoader()
const image = await loader.loadAsync('image.exr')

// find RAW RGB Max value of a texture
const textureMax = await findTextureMinMax(image)

// Encode the gainmap
const encodingResult = encode({
  image,
  // this will encode the full HDR range
  maxContentBoost: Math.max.apply(this, textureMax)
})

// obtain the RAW RGBA SDR buffer and create an ImageData
const sdrImageData = new ImageData(encodingResult.sdr.toArray(), encodingResult.sdr.width, encodingResult.sdr.height)
// obtain the RAW RGBA Gain map buffer and create an ImageData
const gainMapImageData = new ImageData(encodingResult.gainMap.toArray(), encodingResult.gainMap.width, encodingResult.gainMap.height)

// parallel compress the RAW buffers into the specified mimeType
const mimeType = 'image/jpeg'
const quality = 0.9

const [sdr, gainMap] = await Promise.all([
  compress({
    source: sdrImageData,
    mimeType,
    quality,
    flipY: true // output needs to be flipped
  }),
  compress({
    source: gainMapImageData,
    mimeType,
    quality,
    flipY: true // output needs to be flipped
  })
])

// obtain the metadata which will be embedded into
// and XMP tag inside the final JPEG file
const metadata = encodingResult.getMetadata()

// embed the compressed images + metadata into a single
// JPEG file
const jpeg = await encodeJPEGMetadata({
  ...encodingResult,
  ...metadata,
  sdr,
  gainMap
})

// `jpeg` will be an `Uint8Array` which can be saved somewhere

Libultrahdr in Vite

If you import @monogrid/gainmap-js/libultrahdr You will need to exclude it from Vite optimizations.

// vite.config.js

module.exports = defineConfig({
  ...
  optimizeDeps: {
    exclude: ['@monogrid/gainmap-js/libultrahdr']
  },
  ...
})

References

API

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