Chapter 2: HDR ChallengesSee also Chapter 1: Dynamic Range & HDR
To better understand the "Essential HDR Workflow" we need to understand some of the challenges we face creating HDR photos. TerminologyGhostingSince we're taking multiple photos, we don't only have moving elements in a single shot to deal with: any elements that move from between shots will appear "ghosted". The image below shows such a situation.
Note that in this case the ghosting was intentional. Ghosting is not always a bad thing; it always depends on your own goals with your images. That said, generally speaking we try to avoid ghosting as much as we can. Chromatic Aberrations (CA) and FringingChromatic Aberrations (CA)There are several different kinds of Chromatic Aberrations, but here we dealing mainly with Lateral Chromatic Aberration, as it can be reduced using raw development software. Lets first show an example:
HDR ChallengesHDR Challenge: MotionSince we're taking multiple photographs movement is even more of a challenge than it is with single shots. Basically we deal with two types of motion:
Camera MotionFor each single shot you need to take to avoid camera shake. On top of that you also want to make sure that there is no motion between the shots.a) Using a Tripod
Exercise: Try to use a 200mm lens from your tripod and experience the misalignment you get. b) Handheld It's worth noting that we personally shoot a lot of HDR images handheld. The key thing here is to use fast shutter speeds and utilize camera/lens image stabilization. The most critical exposure is the most overexposed frame because it has to have the slowest shutter speed. The best approach is to use the highest continuous frame rate your camera can deliver. The ideal burst rates for the purposes of handheld HDR are 7-10 fps, but we also use slower cameras down to 3fps (in this case the demands for steady alignment are higher though). High frame rates ensure that the camera moves less between shots, and will reduce visible movement (ghosting) within the scene. Perfect AlignmentIt should be clear by now that the key to the best possible results lies in the perfect alignment of all the images shot. In the Essential HDR Workflow chapter we'll share our personal technique to archive this goal. Here is an example what software alignment can do.The following image shows how bad the images were aligned as shot (the image shows the different layers showing through).
At first glance you might think that aligning images using software is a relatively simple task: you just shift the image a bit until it lines up - and in fact this is some implementations actually work. But, naturally, it's never that simple. The camera can move in many ways:
Here is an example of poor alignment:
Often you realize very late in your workflow process that the alignment was less than optimal (the above sample is of course easy to spot) It may be very subtle but we aim always for best possible alignment.
Motion in the SceneCompared to misalignment issues, motion within the scene is far harder to correct (using processes sometime referred to as 'de-ghosting'). You will be surprised how many things move. Motion in the scene means mostly movement between the bracketed shots, and the faster you shoot (i.e. the shorter the time between shots), the fewer elements in the scene can move. Just a few of the potential 'movers' in scenes are listed below:
People and animalsThe good news is that these are often easy to spot, allowing you to take them into account at the point you're actually taking your photos. The bad news is that ghosting created by moving people (and larger animals) are also tough to remove, so the best solution is to analyze the scene carefully while you shoot and avoid them completely if at all possible. Some ghosting in the background (distance) is often perfectly acceptable.Cars and other transportation devicesBeing large, these are equally problematic, but typically are moving a lot faster, meaning you should be able to keep them out of at least some of the frames. Don't try HDR for fast sport :-).FoliageFoliage is extremely tricky because:
Birds or big ButterfliesGhosting of birds or butterflies that fly through the scene look often like sensor dust, so we treat them just like dust (i.e. we remove them using Photoshop's healing brush). Of course if the bird(s) are important to your image you may try some of the de-ghosting options in recent HDR software.FlagsFlags are so common that they are deserve their own category. We recently tried the de-ghosting option in Photoshop CS5 and the result was quite impressive:
CloudsWe don't consider most clouds to be a problem because their ghosting looks just as organic as the original clouds. Of course extremely fast moving clouds can cause some problems. We recently saw some purple artifacts in the clouds using Merge to HDR in CS5. Enabling the de-ghosting feature took care of it.WaterSlow moving or still water (such as creeks and lakes) rarely causes any problems, but we haven't had much luck with strong ocean surf. Trying one of the de-ghosting options may improve the images.HDR Challenge: Chromatic Aberrations (CA)In the introduction of this chapter we explained that CA is a major problem for HDR. The best approach is to remove as much CA as possible in your raw converter. Although some HDR tools can remove CA in theMerge to HDR step, and it helps, we personally try to remove it before merging to HDR.HDR Challenge: Camera NoiseAs mentioned in the last chapter, camera noise is a limiting factor for the dynamic range of our cameras, and the reason to use exposure bracketing is to overcome this limitation. But once we start producing HDR images, we tend to open up the shadows (during tone-mapping) more than we ever did with standard processing. This again reveals the noise. There are, of course, several ways we can minimize the impact of noise on our HDR images:
HDR Challenge: Source Image Formats (Raw or JPEG)JPEG. In our personal work we hardly ever use JPEG images. Why?
If you don't want to deal with raw images, creating HDR images from JPEGs is still a valid technique; you just need to understand the limitations. Raw. With the Raw images you have access to all the information the camera captured. Actually HDR files and raw images are both linear file formats. To be able to view these images both require the application tone curves. Here is a practical dilemma. In the ideal world all "Merge to HDR" operations would start with the linear HDR data. Otherwise the HDR tools have to undo the tone curve operations performed by the raw Converters. This is why quite a few HDR tools offer the option to create HDR directly from raw (mostly using the public domain raw converter dcraw). So why do we prefer to use an external Raw Converter such as Lightroom 3? Simply because we think that in the end these Raw converters allow better control over noise removal, CA removal (e.g. Lens profiles in Lightroom) and lens distortion corrections and offer better de-bayering and custom color profiles (e.g. DNG color profiles via ColorChecker Passport from X-Rite). We always convert to 16 bit TIFF files before the "Merge to HDR" step, and the loss of quality due to the tone curve reversal seems quite acceptable in practice. HDR Challenge: Lens FlareLens flare degrades image quality in certain shooting situations (such as sunsets). This in itself is nothing new, but with HDR we tend more often to include bright light sources into our compositions, which means flare is more prevalent.SummaryYou need to understand these HDR challenges to get the best possible quality. This list is almost certainly incomplete, but hopefully we've covered the main hurdles you'll face. Feedback by our readers is very much welcome.Further learning© 2011, www.dpreview.com & Uwe Steinmueller. |
Thứ Năm, 26 tháng 5, 2011
ARTICLE The art of HDR photography - part 2
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