Bandwidth-efficient HDR WebGL Textures

Storing high dynamic range (HDR) images is a solved problem in general, such as using the excellent OpenEXR format. When is comes to the web, however, there are two major problems. The first is that web browsers don’t support any of the standard HDR image formats, and the second is that HDR images tend to be rather large, which is a problem for conserving bandwidth and reducing load times. Although there are ways to load HDR textures into WebGL using pre-encoded textures and WebGL extensions, this is very bandwidth-inefficient and not supported by all WebGL devices. Thus, the first problem has to be worked around by encoding the HDR image information into standard web images, e.g. JPEG and PNG. The earliest example of this that I can find is the pre-WebGL pfstools HDR HTML viewer, which layers multiple JPEG images at different exposures and blends them with different opacity settings.1 This method was good for its time, since before WebGL image processing calculations were difficult to perform in the browser. However, the method is bandwidth-inefficient as it requires downloading the same image at multiple exposures—five images in the example. This brings us to WebGL, where a method PNG-based method was developed by SpiderGL (and copied by three.js). Although the provided encoder is undocumented, it appears to be based on JPEG-HDR, which uses a tone-mapped base image combined with a subband image that encodes the ratio between the tone-mapped image and the original HDR image.2 The method encodes the tone-mapped image in the RGB channels of a PNG and the ratio in the alpha channel. This works well when lossless compression is desired but is bandwidth-inefficient for photographic textures.

After fiddling around with encoding RGBE as a JPEG and PNG and porting the SpiderGL technique to two separate JPEG images instead of a single PNG image, I stumbled upon a paper describing a better method (which happens to be written by the same person who created the SpiderGL HDR example). The “BoostHDR” technique described in the paper segments the image based on luminance, creating a compression-driven map (CDM), and tone maps the image with different parameters in each segment.3 With the spatial and tone map parameters contained in the CDM, the original HDR image can be recovered from the tone mapped image. The map is stored as a PNG, and the tone mapped image is stored as a JPEG. See the paper for details and figures. I implemented the paper’s encoding scheme in Python, although I left out some of the filtering steps to reduce the script’s external dependencies since the filtering didn’t help much. To display the HDR image in WebGL, both the tone mapped image and CDM image are first loaded using JavaScript, and the CDM is then loaded into the tone mapped image’s alpha channel using the Canvas API. This RGBA texture is then loaded into WebGL, where a fragment shader function is used to recover the HDR image. As one would expect from a photograph encoded as a JPEG versus a PNG, this technique results in files sizes a few times smaller than the SpiderGL method. For lack of a better name, I’m calling this technique “WebHDR.”

A demo can be viewed here. Both the encoder and demo viewer are available on GitHub and have been released into the public domain.

  1. Rafał Mantiuk and Wolfgang Heidrich. “Visualizing high dynamic range images in a web browser”. In: Journal of Graphics, GPU, and Game Tools 14.1 (2009), pp. 43–53. DOI: 10.1080/2151237X.2009.10129276. URL:  

  2. Greg Ward and Maryann Simmons. “JPEG-HDR: A backwards-compatible, high dynamic range extension to JPEG”. In: ACM SIGGRAPH 2006 Courses. ACM, 2006, p. 3. DOI: 10.1145/1185657.1185685. URL:  

  3. Francesco Banterle and Roberto Scopigno. BoostHDR: a novel backward-compatible method for HDR images. 2012. DOI: 10.1117/12.931504. URL:  

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12 Responses to Bandwidth-efficient HDR WebGL Textures

  1. loubna says:

    Thank you so much.
    I did many programs in WebGL but in fact this is my first time when I use Python. I did not understand how to compile the Python file to get the JPG and PNG images.

    Can you help me please? and thanks in advance (sorry for my English).

    • Matthew Petroff says:

      Python is an interpreted language, so it isn’t compiled. To convert a file with the script, run python input-image.exr.

  2. loubna says:

    Thank you so much for your response. In fact I did some tests and I got good results on some photos, but in others there are some blue tasks when I display the photo in webgl.

    In fact I used Photomatix to merge and generate hdr images, then I have stored them in the format (.exr) but I don’t understand why the blue tasks appears on some images.

  3. loubna says:

    See this the link if you want see my results.

    Thanks in advance

    • Matthew Petroff says:

      I finally got a chance to look at this. It turns out that there was a bug in handling images that contained zeros; I just fixed this, so it should work now if you update your copy. As a side note, the image in question did not appear to have enough dynamic range to need this technique.

  4. Nina says:

    I tried to create HDR image using HDR Tools ( beacause my project need to create HDR image using command line.I have stored the result into .exr format. but when I use your Python script to generate the cmd card and tone mapped image, I get the following errors: raise IOError (jpeg does not support alpha channel)?
    Is there a way to treat this problem without convert .exr file?

  5. Nina says:


    I tried to store the tone mapped image into gif format instead jpg format (because gif format support transparent) and I get good results.

    According to you.Is true what i did? thanks for your response

    • Matthew Petroff says:

      It may work, but it’s certainly not bandwidth or space efficient (GIFs have poor compression). At the very least, use a PNG. Removing the alpha channel and using a JPEG, is still much better.

  6. Nina says:

    Thanks for your response. Is there a way to remove alpha channel from exr file? If not how to convert a png file to jpg using python and imageio?

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