Understanding modern HDR Photography, a set of tools, links, examples and explanations


This is a follow-up post to my previous post which was viewed over 167000 in the span of a few hours. This is part of a series of articles on HDR photography. This article continues the theme of the 1st article by giving further tools, tricks, links and explanation of HDR photography. This article can also be seen as a continued photographical revue of HDR photography since all images included are HDR photos.

  1. Modern HDR photography, a how-to
  2. How The Memoirs got 167000 hits in few hours…
  3. The Memoirs were viewed 170000 times yesterday
  4. Understanding modern HDR Photography, a set of tools, links, examples and explanations <- You are here


This is the 4th article in a series of articles on HDR Photography. The 1st article was a guide to Modern HDR photography. The second article delved into how that article had been viewed 167000 times in a day. The 3rd article examined the why, how exactly did the mechanics of this article make it so popular.

You can also see this article as a further revue of HDR Photography, since all photos included here are HDR photos. This article in this series will continue further tools and techniques for HDR photography. All the photos in this post were found in the HDR pool from flickr. Please visit it or click on the images to see them at full size.



Introduction to HDR and a short Photoshop tutorial

Photoshop Tutorial for HDR

A good FAQ on HDR photography from the makers of Photomatix

* * * * *

The following article explains the basic precepts of HDR photography in digital photography. This guide is a courtesy of cambridgeincolour. Cambridgeincolour has a vast database of tutorials on photography, I encourage you to visit it.

* * * * *






Dynamic range in photography describes the ratio between the maximum and minimum measurable light intensities (white and black, respectively). In the real world, one never encounters true white or black– only varying degrees of light source intensity and subject reflectivity. Therefore the concept of dynamic range becomes more complicated, and depends on whether you are describing a capture device (such as a camera or scanner), a display device (such as a print or computer display), or the subject itself.
Just as with color management, each device within the above imaging chain has their own dynamic range. In prints and computer displays, nothing can become brighter than paper white or a maximum intensity pixel, respectively. In fact, another device not shown above is our eyes, which also have their own dynamic range. Translating image information between devices may therefore affect how that image is reproduced. The concept of dynamic range is therefore useful for relative comparisons between the actual scene, your camera, and the image on your screen or in the final print.


Light intensity can be described in terms of incident and reflected light; both contribute to the dynamic range of a scene (see tutorial on “camera metering and exposure“).

Strong Reflections Uneven Incident Light

Scenes with high variation if reflectivity, such as those containing black objects in addition to strong reflections, may actually have a greater dynamic range than scenes with large incident light variation. Photography under either scenario can easily exceed the dynamic range of your camera– particularly if the exposure is not spot on.

Accurate measurement of light intensity, or luminance, is therefore critical when assessing dynamic range. Here we use the term illuminance to specify only incident light. Both illuminance and luminance are typically measured in candelas per square meter (cd/m2). Approximate values for commonly encountered light sources are shown below.

Here we see the vast variation possible for incident light, since the above diagram is scaled to powers of ten. If a scene were unevenly illuminated by both direct and obstructed sunlight, this alone can greatly increase a scene’s dynamic range (as apparent from the canyon sunset example with a partially-lit cliff face).


Although the meaning of dynamic range for a real-world scene is simply the ratio between lightest and darkest regions (contrast ratio), its definition becomes more complicated when describing measurement devices such as digital cameras and scanners. Recall from the tutorial on digital camera sensors that light is measured at each pixel in a cavity or well (photosite). Each photosite’s size, in addition to how its contents are measured, determine a digital camera’s dynamic range.

Photosites can be thought of as a buckets which hold photons as if they were water. Therefore, if the bucket becomes too full, it will overflow. A photosite which overflows is said to have become saturated, and is therefore unable to discern between additional incoming photons– thereby defining the camera’s white level. For an ideal camera, its contrast ratio would therefore be just the number of photons it could contain within each photosite, divided by the darkest measurable light intensity (one photon). If each held 1000 photons, then the contrast ratio would be 1000:1. Since larger photosites can contain a greater range of photons, dynamic range is generally higher for digital SLR cameras compared to compact cameras (due to larger pixel sizes).

Note: In some digital cameras, there is an extended low ISO setting which produces less noise, but also decreases dynamic range. This is because the setting in effect overexposes the image by a full f-stop, but then later truncates the highlights– thereby increasing the light signal. An example of this is many of the Canon cameras, which have an ISO-50 speed below the ordinary ISO-100.

In reality, consumer cameras cannot count individual photons. Dynamic range is therefore limited by the darkest tone where texture can no longer be discerned; we call this the black level. The black level is limited by how accurately each photosite can be measured, and is therefore limited in darkness by image noise. Therefore, dynamic range generally increases for lower ISO speeds and cameras with less measurement noise.

Note: Even if a photosite could count individual photons, it would still be limited by photon noise. Photon noise is created by the statistical variation in arrival of photons, and therefore represents a theoretical minimum for noise. Total noise represents the sum of photon noise and read-out noise.

Overall, the dynamic range of a digital camera can therefore be described as the ratio of maximum light intensity measurable (at pixel saturation), to minimum light intensity measurable (above read-out noise). The most commonly used unit for measuring dynamic range in digital cameras is the f-stop, which describes total light range by powers of 2. A contrast ratio of 1024:1 could therefore also be described as having a dynamic range of 10 f-stops (since 210 = 1024). Depending on the application, each unit f-stop may also be described as a “zone” or “eV.”


Scanners are subject to the same saturation:noise criterion as for dynamic range in digital cameras, except it is instead described in terms of density (D). This is useful because it is conceptually similar to how pigments create tones in printed media, as shown below.

The overall dynamic range in terms of density is therefore the maximum pigment density (Dmax), minus the minimum pigment density (Dmin). Unlike powers of 2 for f-stops, density is measured using powers of 10 (just as the Richter scale for earthquakes). A density of 3.0 therefore represents a contrast ratio of 1000:1 (since 103.0 = 1000).

Instead of listing total density (D), scanner manufacturer’s typically list just the Dmax value, since Dmax – Dmin is approximately equal to Dmax. This is because unlike with digital cameras, a scanner has full control over it’s light source, ensuring that minimal photosite saturation occurs.

For high pigment density, the same noise constraints apply to scanners as digital cameras (since they both use an array of photosites for measurement). Therefore the measurable Dmax is also determined by the noise present during read-out of the light signal.


Dynamic range varies so greatly that it is commonly measured on a logarithmic scale, similar to how vastly different earthquake intensities are all measured on the same Richter scale. Here we show the maximum measurable (or reproducible) dynamic range for several devices in terms any preferred measure (f-stops, density and contrast ratio). Move your mouse over each of the options below to compare these.

Note the huge discrepancy between reproducible dynamic range in prints, and that measurable by scanners and digital cameras. For a comparison with real-world dynamic range in a scene, these vary from approximately 3 f-stops for a cloudy day with nearly even reflectivity, to 12+ f-stops for a sunny day with highly uneven reflectivity.

Care should be taken when interpreting the above numbers; real-world dynamic range is a strong function of ambient light for prints and display devices. Prints not viewed under adequate light may not give their full dynamic range, while display devices require near complete darkness to realize their full potential– especially for plasma displays. Finally, these values are rough approximations only; actual values depend on age of device, model generation, price range, etc.

Be warned that contrast ratios for display devices are often greatly exaggerated, as there is no manufacturer standard for listing these. Contrast ratios in excess of 500:1 are often only the result of a very dark black point, instead of a brighter white point. For this reason attention should be paid to both contrast ratio and luminosity. High contrast ratios (without a correspondingly higher luminosity) can be completely negated by even ambient candle light.


The human eye can actually perceive a greater dynamic range than is ordinarily possible with a camera. If we were to consider situations where our pupil opens and closes for varying light, our eyes can see over a range of nearly 24 f-stops.

On the other hand, for accurate comparisons with a single photo (at constant aperture, shutter and ISO), we can only consider the instantaneous dynamic range (where our pupil opening is unchanged). This would be similar to looking at one region within a scene, letting our eyes adjust, and not looking anywhere else. For this scenario there is much disagreement, because our eye’s sensitivity and dynamic range actually change depending on brightness and contrast. Most estimate anywhere from 10-14 f-stops.

The problem with these numbers is that our eyes are extremely adaptable. For situations of extreme low-light star viewing (where our eyes have adjusted to use rod cells for night vision), our eyes approach even higher instantaneous dynamic ranges (see tutorial on “Color Perception of the Human Eye“).


Even if one’s digital camera could capture a vast dynamic range, the precision at which light measurements are translated into digital values may limit usable dynamic range. The workhorse which translates these continuous measurements into discrete numerical values is called the analog to digital (A/D) converter. The accuracy of an A/D converter can be described in terms of bits of precision, similar to bit depth in digital images. The A/D converter is what creates values for the digital camera’s RAW file format.

Bit Precisionof Analog/Digital Converter Contrast Ratio Dynamic Range
f-stops Density
8 256:1 8 2.4
10 1024:1 10 3.0
12 4096:1 12 3.6
14 16384:1 14 4.2
16 65536:1 16 4.8

Note: Above values are for A/D converter precision only,

and should not be used to interpret results for 8 and 16-bit image files.

Furthermore, values shown are a theoretical maximum, assuming noise is not limiting.

As an example, 8-bits of tonal precision translates into a possible brightness range of 0-255 (since 28 = 256 levels). Assuming that each number is proportional to actual image brightness (meaning twice the pixel value represents twice the brightness), 8-bits of precision can only encode a contrast ratio of 256:1, or 8 f-stops.

Most digital cameras use a 10 to 14-bit A/D converter, and so their theoretical maximum dynamic range is 10-14 stops. However, this high bit depth only helps minimize image posterization since total dynamic range is limited by noise levels. Similar to how a high bit depth image does not necessarily mean that image contains more colors, if a digital camera has a high precision A/D converter it does not necessarily mean it can record a greater dynamic range. In practice, the dynamic range of a digital camera does not even approach the A/D converter’s theoretical maximum; 5-9 stops is generally all one can expect from the camera.


Can digital image files actually record the full dynamic range of high-end devices? There seems to be much confusion on the internet about the relevance of image bit depth on recordable dynamic range.

We first need to distinguish between whether we are speaking of recordable dynamic range, or displayable dynamic range. Even an ordinary 8-bit JPEG image file can conceivably record an infinite dynamic range– assuming that the right tonal curve is applied during RAW conversion (see tutorial on curves, under motivation: dynamic range), and that the A/D converter has the required bit precision. The problem lies in the usability of this dynamic range; if too few bits are spread over too great of a tonal range, then this can lead to image posterization.

On the other hand, displayable dynamic range depends on the gamma correction implied by the image file, or used by the video card and display device. Using a gamma of 2.2 (standard for PC’s), it would be theoretically possible to encode a dynamic range of nearly 18 f-stops (see tutorial on gamma correction, to be added). Again though, this would suffer from severe posterization. The only current standard solution for encoding a nearly infinite dynamic range (with no visible posterization) is to use high dynamic range (HDR) image files in Photoshop CS2 (or other supporting program).


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Previous: The Memoirs were viewed 170000 times, an analysis

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24 responses to “Understanding modern HDR Photography, a set of tools, links, examples and explanations”

  1. charles ravndal Avatar

    I really like the first picture since I am always a sucker for nature pictures. I wish I am quite proficient with camera use and techniques

  2. range Avatar

    Yeah, HDR rocks.

  3. psychspirit Avatar

    wow. There’s a nostalgic element to this image. I’m so out of the loop, what is HDR photography?

  4. range Avatar

    Hi Psychspirit and welcome to The Memoirs.
    HDR = High Dynamic Range, sometimes called HDRI, I for Imaging.

    Yes there is something nostalgic about that photo. HDR photography is a way to capture more details when you normally couldn’t. It’s for underexposed shots and overexposed shots, where you want to capture a lot of details. You start out with a tripod, a digital camera. You take 2-7 photos of the same subject at different apertures. You then use Photoshop or Photomatix to combine all these images into one. By varying the exposure and the shutter speed, you capture different colors and moments. When they are combined, they give a touch of hyperrealism to your pictures or a touch of unreality, because there are so many colors.

    You can visit:

    and read the articles under HDR photography. The second one in the first post on the subject is a step by step tutorial on how to produce a HDR image. The 2nd and 3rd post can be viewed as an photographical HDR revue of the most recent photos off flickr in the HDR pool.


  5. Nome Avatar

    I still don’t understand the technology, but the photos are beautiful.

    Oh, and the Queer Chef says hi.

    Have a nice day!

  6. range Avatar

    Hi Nome, welcome to The Memoirs!
    Yes they are quite beautiful.

  7. Mr Angry Avatar

    Another great article Range, I can see a book coming out of this. Go the angry alliance! How about video tutorials for youtube? That would probably be a lot of work, more than a one man job. If we weren’t on opposite sides of the globe I’d suggest teaming up 🙂

    As an aside, did you get any downward correction in your site stats? Over the weekend my blog page was showing almost 10,000 extra hits inexplicably that didn’t match the daily stats. This was corrected today -it’s back to its correct level. A little bit of weirdness.

  8. range Avatar

    Well thanks for your comments, the Angry Alliance rules!

    Yeah my blog stats are on the fitz today, they said that it would be fixed within 24 hours.

    A YouTube guide could be interesting. Teaming up is a good way of going about things, even if we are a long way apart. internetweb might help with, send me an email pur_ho [at] hotmail [dot] com.

  9. Sandra Avatar

    You boys keep doing your thing and I’ll keep being your cheer leaders. The pics are beautiful Range. I’ll take a copy of this one. 😀 for mothers day please.

  10. range Avatar

    Thanks Sandra!

  11. […] HDR Tutorial (Photomatix) FAQ – HDR images for Photography Understanding modern HDR Photography Flickr HDR pool […]

  12. john Dengate Avatar
    john Dengate

    Any thoughts on how this process would work for interior panoramic photographs. Blow out windows are always a problem when trying to balance the panos.

  13. Bruce Avatar

    Hey Range,

    HDR digital photography sounds great and interesting to say the least. Judging by the dates of the last responses, everyone on this comment page has vanished by now. I hope I’m not typing to myself? I kind of understand the concept of HDR but am sure I have much to learn. Just for my info, what kind of digital camera do you suggest I use for this kind of work? I mean specifically? I’d like to use some of the content on this blog on my own digital photography blog. All rights would go to you of course. What do you think? My blog is new and I intend to put really good content on it. Please let me know. Thanks

  14. range Avatar

    Hi Bruce. You can do HDR photography with any DSLR. I prefer Nikons and have just gotten myself a Nikon D200 and plan on taking some HDR photos in the next couple of weeks. I have seen some mighty impressive HDR photos taken with a Nikon D50. Once you get used to the groove, and how to combine the images, it should be pretty easy. Photoshop is an obvious choice to blend the images together. I am actually looking forward to trying HDR without a tripod with a VR Nikkor lens. Should be interesting.

    As per the reprints of the material on this blog, be advised that I actually reprinted the articles of other authors on this site with their permission. You will have to contact them yourself to obtain rights.

    As for any original content on my blog, I prefer if you use a short quote and link back to my blog.

    Welcome to The Memoirs.

  15. luis Avatar

    hi, i am from mexico and i got a simply question that i just don understand.

    i am working whit hdr, i know how to use it but i dont know what tonal hierachy?

    i will be gald if you could give me a site or explain me clearly that point.


  16. range Avatar

    By taking HDR photographs, you are actually violating tonal hierarchy, because you are essentially compositing photos at differing exposures to achieve a visual range not possible thus violating tonal hierarchy.

    From cambridge in color


    In contrast to the other three conversion methods, the local adaptation method does not necessarily retain the overall hierarchy of tones. It translates pixel intensities not just with a single tonal curve, but instead also based on the surrounding pixel values. This means that unlike using a tonal curve, tones on the histogram are not just stretched and compressed, but may instead cross positions. Visually, this would mean that some part of the subject matter which was initially darker than some other part could later acquire the same brightness or become lighter than that other part– if even by a small amount.

    A clear example where global tonal hierarchy is not violated is the example used in the page on using a GND to extend dynamic range (although this is not how local adaptation works). In this example, even though the foreground sea foam and rock reflections are actually darker than the distant ocean surface, the final image renders the distant ocean as being darker. The key concept here is that over larger image regions our eyes adjust to changing brightness (such as looking up at a bright sky), while over smaller distances our eyes do not. Mimicking this characteristic of vision can be thought of as a goal of the local adaptive method– particularly for brightness distributions which are more complex than the simple vertical blend in the ocean sunset above.

    An example of a more complex brightness distribution is shown below for three statue images. We refer to contrast over larger image distances as global contrast, whereas contrast changes over smaller image distances are termed local contrast. The local adaptation method attempts to maintain local contrast, while decreasing global contrast (similar to that performed with the ocean sunset example).

    The above example illustrates visually how local and global contrast impact an image. Note how the large-scale (global) patches of light and dark are exaggerated for the case of high global contrast. Conversely, for the case of low global contrast the front of the statue’s face is virtually the same brightness as it’s side.

    The original image looks fine since all tonal regions are clearly visible, and shown with sufficient contrast to give it a three-dimensional appearance. Now imagine that we started with the middle image, which would be an ideal candidate for HDR conversion. Tonal mapping using local adaptation would likely produce an image similar to the far right image (although perhaps not as exaggerated), since it retains local contrast while still decreasing global contrast (thereby retaining texture in the darkest and lightest regions).

  17. jim austin Avatar
    jim austin


    Did you ask the artists on Flickr for permission to use their hdr pictures ?


  18. range Avatar

    Jim, most of the photos of my HDR related posts are posted using the blog this feature from flickr. I have not used any photos that I couldn’t use. It is my understanding that they are used in a Creative Commons license. Please read my disclaimer if you have any problems with any of my uses or inform me if anyone wishes me not to use their photos.

    Since then, I have also added photo credit at the bottom of all of my posts to the artists whose photos I use. But I have not been using any photos from flickr for a while, since I am showcasing my own.


  19. […] 5-6 ступеней, матрицы цифровой камеры – теоретически от 8 до 11 ступеней, хотя на практике большинство цифровых […]

  20. grasshopper Avatar

    Thanks for explaining HDR, it seems like it the next step for amateur photographers like myself. Although it seems like I’d have to invest in Photoshop to do it right. What program do you use to process your pics?

    The Grasshoper from Maui.

  21. range Avatar

    Hey Grasshopper! Wow, in Maui, you’ll have great opportunities to use HDR! The easiest software to use is Photomatix, which is a lot cheaper than Photoshop.

    If you know a student or are a student, the student edition of PS is a lot cheaper. There are also other ways of getting that software.

  22. […] ступеней, матрицы цифровой камеры – теоретически от 8 до 11 ступеней, хотя на практике большинство цифровых […]

  23. HDR и с чем его едят | Фотография для души. Блог о фотографии Avatar

    […] матрицы цифровой камеры – теоретически от 8 до 11 ступеней, хотя на практике большинство цифровых […]

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