The High Dynamic Range Landscape Photography Tutorial (49p).pdf

Published July 2006

The High Dynamic Range (HDR) Landscape Photography Tutorial

Table of Contents

1. Overview

The Situation

A New(-ish) Approach

2. What is HDR?

Definition of HDR

HDR vs. 8- or 16-bit Formats

Capturing HDR Image Data

What Is HDR Good For?

3. Setting Up the Input Images

Physical Setup

Camera Setup

Determining the Exposure Sequence

RAW Conversion

Single Frame Scenes vs. Multi-frame Stitched Panoramas

4. Processing a Single Frame HDR Image

Tools Used

Workflow 1 – Photoshop CS2

Workflow 2 – Photomatix Pro

Comparison of Workflow Results

5. Processing a Multi-Frame Stitched HDR Image

Tools Used

Differences from the Single Frame Workflow

Workflow Overview

6. Gallery of HDR Images

7. Conclusion

Wish List

References

1. Overview

As a wildlife and landscape photography enthusiast with a couple of years of serious digital shooting under my belt, I do not

claim to be an expert with High Dynamic Range (HDR) imaging or photography in general. But I have fun in the field, enjoy

learning as much as I can about the art and science of photography, and have produced some images that are personally

rewarding, as well as enjoyed by others. I currently derive particular satisfaction from working with stitched panoramas taken at

sunrise or sunset, printed on roll stock.

Late in 2005 I began adding HDR processing into my workflow. This was done to gain greater access to the tonality present in

wide and dramatically lit vistas. I mostly bypassed the usual digital exposure blending route as it seemed labor intensive,

although I know the technique can produce results. Naturally I posted several HDR images to Naturescapes.Net (NSN), and

several people expressed interest in the technique used to create these images. At the request of the NSN editorial team, I

organized my learning and thinking about HDR, and this article is the result.

For at least a few of those who read this, I hope for two things. First, I would like to add some fuel to your own creative fires in

working with HDR images. Second, I hope you will post your results and share questions, ideas and techniques that work for

you. There is still much to learn as this new imaging capability, its tools, and our creative use matures.

The Situation

Say I have an image that looks like this:

I captured the image at sunrise, a great time to be out in the field. My senses soaking up everything before me, I tripped the

shutter, hoping to capture an image that would evoke wonder and appreciation – a hint of the moment.

Back at my workstation, I eagerly began sorting through the captures. However, despite the presence of a fair amount of

dramatic light and lots of interesting tonality and detail across the original scene, images like the one above just do not evoke

the experience. The clouds lack drama, detail and color; portions of the sky are far over-exposed; distant trees have turned to a

muddy blur; and the ice does not reveal the snappy surface detail it showed in the early morning glow.

Of course, I realized while out shooting that there was a lot of contrast (or “dynamic range”) in the scene, and that the camera

could only capture a small subset of that range. So I shot different exposures (“bracketing”), some optimized for the sky, some

for the foreground ice, others for the far, shadowy trees. Not surprisingly, none of these single images really grabs me upon

review.

I considered that I could use a graduated neutral density filter in situations like this. At capture time, these filters are used to

block some light in the brightest part of the frame, often the sky. This effectively expands the captured dynamic range by one to

three stops. Of course that does not help now, with images that I have already taken. And considering the irregular line of the

mountains and the dynamic range reflected across the ice and water, I am unsure if filters would be workable for this scene.

Using an exposure blending technique, I could combine several digital files with different exposures of the scene. It seems

worth trying, so I put in some effort with three exposures taken across a 4-stop range using automatic exposure bracketing.

The images are layered, luminance masked and blended in Photoshop CS2, together with some curves and contrast

enhancements. This produced the following image:

This is a definite improvement, and with more work I could fine tune this image further. For example, some ghosting in the

moving clouds could be cloned or masked out, more work with contrast and curves could increase the drama in the clouds,

some selective saturation or white point adjustments could improve the whites of the ice and snow, and so on. The exposure

blending technique is used to good effect by many photographers, but it can mean a lot of work. And I feel it will leave me

wanting more from this image.

A New(-ish) Approach

Even with all of the above techniques, plus a lot of effort, the results may not have maximum impact. Perhaps you, like me,

have wondered if there is another way. Enter High Dynamic Range (HDR). HDR imaging has been around for at least a couple

of decades, but has been popularized more recently by new software tools.

Using one such tool, the Photomatix Pro HDR processing application, I tried again with the example image. On the same three

bracketed exposures, I can produce this image:

This result better represents the feeling I had at the scene, represented by the title “Stormy Sunrise.” As a bonus, creating this

image required no use of filters in the field, and minimal fine tuning work in Photoshop. The heavy lifting was done by “tone

mapping,” a process of converting an HDR image back into an 8-bit or 16-bit image file that can be worked with conventionally

(as the HDR image itself can not). In total it took less than 30 minutes of processing time after converting the RAW files –

significantly less time than for the blended exposure version of the image, which honestly still needs more work.

The HDR image reveals more of the original scene’s drama than does the exposure blended version. More detail is visible

throughout the sky, mountains and ice, in large part due to what are called local contrast enhancements – adjustments that

emphasize tonal transitions and details within a very small space rather than strictly preserving the overall relationship of bright

and dark tones across the entire image. Overall contrast and color tone is more expressive.

As for the original single frame with its middle-of-the-road, neutral exposure? While it could be tweaked, it is not remotely in the

same league for expressing the impact of the original scene.

To see how you can use HDR as part of your workflow to create images with a large dynamic range, read on! This article gives

a landscape photographer’s view of the theory behind HDR, describes how to capture the input images, and shows how to use

two popular HDR tools: Photoshop CS2 and Photomatix Pro. It will also show how to use these tools to process both single

frames and stitched panoramic images.

2. What is HDR?

Before getting into the tutorial, it would help to have some terms of reference. In brief, dynamic range (DR) is the range of

luminance values from the darkest to the brightest. The original, real-world scene has a certain inherent DR which may be

quite large – a ratio of 100,000:1 or more as DR is measured. Your eyes can perceive a subset of the scene’s DR (about

10,000:1), while your camera can record a smaller subset than your eyes can see – perhaps 400:1 for a DSLR. The DR of a

monitor or a printed photograph is smaller yet.

High dynamic range (HDR) in photography means representing the full range of tonality present in the scene with high

perceptual faithfulness. Most HDR techniques currently use software to combine several different exposures of a scene into a

single file that maps the full range of luminance at every pixel. This HDR image is then processed in various ways depending

on the ultimate usage. For most of us this means tone mapping the HDR image into a 16-bit or 8-bit digital file such as a JPEG

or TIFF image.

If this is enough definition for you and you want to get into the part that shows how to get things done, feel free to skip ahead to

the next section on shooting technique. The rest of this section provides the details of what HDR is for those who prefer to

know “what” before getting into the “how”.

Key points covered in the rest of this section:

z Definition of HDR

z HDR vs. 8-bit or 16-bit file formats

z Capturing HDR images

z What is HDR good for?

Definition of HDR

Dynamic range (DR) is a fairly generic term used in a variety of disciplines. As described above, for our purposes in

photography, DR is the range of luminance values from the darkest to the brightest . The DR of the real-world scene in

front of you is the range of darkest to brightest portions available to your eye, film or imaging sensor. The DR of a camera is

the subset of the scene’s DR that can be captured without being clipped on the highlight end, or reduced to noise or outright

blocked up on the shadow end. Conversely, the DR of a monitor is the luminance range it can display from black to white.

High dynamic range (HDR) must mean a lot of DR. But how much is “a lot?” The standard unit for measuring luminance is

candelas per square meter, or cd/m2. You may have seen this unit used in monitor specifications. According to the FAQ at

www.hdrsoft.com (the web site for Photomatix Pro), “the luminance of starlight is around 0.001 cd/m2, that of a sunlit scene is

around 100,000 cd/m2, [… and] the luminance of the sun itself is approximately 1,000,000,000 cd/m2.”

Without getting into the debates about which medium truly has precisely what DR, this chart summarizes some rule-of-thumb

DR values for different stages of dealing with a scene:

STAGE

DYNAMIC RANGE

STOPS

Typical outdoor, sunlit scene

100,000:1 or more

~17 EV

Human eye

10,000:1

~14 EV

Film camera

up to ~2000:1

~11 EV

Digital camera

typically ~400:1

~8.5 EV

Good computer monitor

500:1 to 1000:1

9 - 10 EV

Typical photo print

100:1 up to 250:1

7 - 8 EV

One clear conclusion from this chart is that the experience of seeing the original scene, then capturing it, to reproducing it for

others to see, is one of progressively losing DR. DR lost at capture time is gone for good, as it can never be regained after that

point. If it can be captured as close as possible to what was present in the original scene, then perhaps something can be done

to present the image to viewers with a better interpretation of the source scene’s tonality and detail.

Loosely speaking, then, HDR is the ability to capture and represent the full DR found in a scene with high perceptual

accuracy and precision . To pin it down further, we need to look at digital file formats and how they represent luminance

values.

Norman Koren’s web site has a good discussion of some of this information, specifically DR from digital capture through

reproduction on screen or in print; see www.normankoren.com/digital_tonality.html . Sean McHugh’s web site also has a lot of

good information about this subject; see for example www.cambridgeincolour.com/tutorials/dynamic-range.htm .

HDR vs. 8- or 16-bit Formats

An HDR image is represented using what can be considered a 32-bit per RGB channel format. The 32-bit numbers are decimal

(or “floating point”) values, not integer values. The format records the luminosity of every point in the source scene, regardless

of its level of brightness. There are several different HDR file formats in existence, including Radiance RGBE and Open-EXR.

Each format encodes image data in a different way, with corresponding advantages and disadvantages.

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