Hasselblad X2D II 100C: the first true end-to-end HDR camera

There may be no camera brand no more legendary than Hasselblad. They have been making incredible cameras for 184 years! That isn’t a typo. That’s 7 years before Florida was a state, 47 years before Kodak, and 121 years before NASA starting using Hasselblad in outer space. This isn’t a company that just knows how to make great cameras, this is a company that knows how to adapt and innovate at the highest levels. And now, they’ve adapted again for the future of photography.

Today, they just launched the Hasselblad X2D II 100C with numerous advancements over its predecessor, including the first end-to-end HDR camera. They call it “HNCS HDR” (Hasselblad Natural Colour Solution with High Dynamic Range).

Hasselblad HDR support includes:

  • The first HDR OLED touchscreen (1400-nit peak brightness) to actually view images in HDR on the camera
  • Capture images natively in HDR formats including JPG with ISO gain map or HEIF.
  • 15.3 stops of dynamic range with 16-bit depth

I haven’t had a chance to use one of these cameras, but I wonder if native HDR capture might also mean a more accurate in-camera histogram. Nearly all cameras show a histogram of the in-camera’s JPG rather than the RAW data. Perhaps this camera will show the histogram for the HEIF, which should include the full dynamic range (likely encoded as HLG). If so, that could increase the real world dynamic range even further as most photographers are prone to exposure error given the very limited quality of a JPG histogram and blinkies.

The X2D II 100C also features:

  • 102 megapixels with the low noise characteristics you’d expect from medium format.
  • 5-Axis, 10-Stop stabilisation.
  • LiDAR and a new new AF illuminator for fast, accurate focusing in a wide range of light.
  • 1TB of built-in SSD storage, with a CFexpress Type B slot for additional storage via memory cards.
  • Continuous autofocus (a first for Hasselblad) and other new autofocus modes.
  • A refined look and controls for better appearance and ergonomics.

I haven’t had the opportunity to see one of these cameras in person, but I’ve spent gone through their press release, marketing material, and sample images in depth to get a good sense of Hasselblad’s approach to HDR. Below are my first impressions of this very interesting new camera.

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What are the benefits of Hasselblad HDR?

The star of the show here may be the new 1400-nits HDR OLED touchscreen. That puts it in a range very similar to the iPhone, which offers excellent HDR in nearly all conditions other than outdoors in bright light. Depending on how they’ve designed the in-camera firmware and how the display is adapted for ambient light, I imagine this may offer as much as 3 stops of HDR display.

That would be incredible to properly see the real image and visualize highlights without clipping or rolloff. This should be very useful in a wide range of conditions (though you should expect 0 headroom in bright outdoor conditions, as you would with an iPhone – as you’d probably need 3-10,000 nits for bright outdoor HDR). I’ll be very curious to get my hands on one of these to try. And if you purchase one, please comment below on your experience.

 

The next most significant benefit is image quality. With 15.3 stops dynamic range, 16-bit color, and the inherently low noise characteristics of medium format, there is probably no camera more capable of supporting both the best HDR displays and prints from a single RAW file. The key benefit here is likely in shadows, where you can expect much cleaner results in an image properly exposed to retain highlight detail.

 

The support to capture images natively in HDR formats is very welcome. This should help further demonstrate how quickly HDR is moving towards being a mainstream format and the optimal choice for highest image quality. This adds to a wide range of brands offering native HDR capture as JPG gain maps or HEIF (including Nikon, Canon, Sony, Fuji, Olympus, Sigma, iPhone, Android, and likely others).

Native HDR capture is great for those who wish to go directly from camera to display. Realistically, the best HDR results will always come from shooting RAW, as JPG and HEIF are meant for final display and not ideal formats for further editing. Additionally, native HDR capture is limited to certain camera modes (including exposure / focus bracketing, continuous shooting, manual exposure, or if using a Nikon flash).

 

How is the HDR image quality?

Hasselblad has not shared RAW versions of images corresponding to their HDR samples, so it is impossible to compare directly. They have a long history of outstanding RAW images and I have little doubt that these are probably the best RAW files you can possible capture to create HDR images. However, one of their customers did send me a few RAW images from this new camera. The files were roughly 210MB, as you’d expect for a camera with such high resolution. The detail was outstanding and noise levels in shadows looked very good (shot at ISO 100, a little above the base ISO of 50). Overall, I would say the RAW images I saw looked extremely promising, as you’d expect from Hasselblad.

 

Hasselblad has shared several sample HDR JPG images (no HEIF samples). While their website refers to “UltraHDR” (which is typically associated with the legacy Android encoding), these images are actually encoding using the ISO 21496-1 gain map standard (without redundant Android XMP). This is ideal and exactly what they should do, it may just be a bit confusing to those who understand the technical difference between UltraHDR and ISO HDR.

Even though they include all 102 megapixels, these HDR JPGs are only 7-21 MB in size (with most of the samples 10 or less). I expect you should be able to choose from a range of sizes if you prefer to capture smaller files or lower resolution.

The HDR JPGs show up to 3 stops of encoded HDR headroom (you could easily edit to higher values). Highlight rolloff looks very good in areas where extreme highlights will inevitably clip. Sunsets show great color and detail. Skin tones show restoration of normal color in the range where light skin tones will turn grey in SDR. Color and detail appear well managed across a variety of subjects, and of course you can assert even more control by processing the RAW as HDR.

Most importantly, I think they have done a much better job creating a natural HDR result than I typically see with a camera phone such as an iPhone. This has nothing to do with sensor characteristics, its the artistic intention. An HDR image should show shadows and midtones which are very close to the values in the SDR image, as SDR is a severe compromise of the highlights and that’s what HDR resolves. With a smart phone, you typically see midtones processed far too bright, which is one of the reasons some viewers on Instagram complain that the HDR images they see are “too bright”. A properly edited HDR image should not appear too bright, the extra brightness should primarily just be used to enhance highlight color and detail, not make the image brighter overall. Kudos to Hasselblad for their excellent default HDR processing.

The gain maps are encoded with full color, which is ideal. However, the map also uses 420 color sub-sampling, which is technically incorrect (as a gain map is just a bunch of math and the assumptions underlying color sub-sampling do not apply to these pseudo images). I have seen some examples where this can produce notable artifact (such as noise in blue skies). I don’t see evidence of that in these limited samples and if Hasselblad has designed the encoding with awareness of this issue, they may have taken steps to mitigate the risks that can cause issues (and therefore avoiding the increased file size of a 444 map). It’s not a concern for me. This won’t affect you at all if you shoot RAW (which you should) and Hasselblad could issue a firmware update if real world issues are later found with this encoding.

 

Overall, this appears to be a very promising leap forward for a premium camera from a legendary brand. It’s incredible to see their adoption and innovation around HDR, and look forward to trying one in person in the future.

The X2D II 100C is available from B&H with body-only or with a 75m lens bundle (which is similar to a 59mm on a 35mm camera).

See Hasselblad’s product page and sample images for more info.

 

 

New in Adobe Camera RAW 17.5: automatically remove dust from photos

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Sensor dust in your RAW photos can be a huge hassle. It can take a lot of time to clean up manually, and you might wreck a print if you don’t notice subtle spots until you’re viewing a large image on your wall. Adobe Camera RAW (ACR) v17.5 just added an incredible new tool to take care of this in 1-click: AI dust removal.

How good is it? I’ve tried it with dozens of photos and the results are incredible. It finds and flawlessly fixes at least 90-95% of the dust spots in my photos. And more importantly, it almost never causes artifacts or a bad result. So if it fails, it does so safely and I don’t worry about creating new problems. I just do a quick review to see if I might need to manually remove a few dust spots it missed.

You can use the dust removal in your RAW smart object, or by using the Camera Raw Filter. The filter approach is very handy for several reasons:

  • You can apply it to any image (not just RAW content).
  • It can often do a better job (as shown in the video), as the results are not the same as processing the RAW.
  • And if there are any mistakes, you can apply it locally by using a filter mask to only apply the dust removal where it improves the image.

The best workflow to use this new tool is:

  • Consider using Camera RAW Filter rather than fixing in the RAW, as this allows for more local control and often better initial results.
  • Go to the remove tab in ACR, open the new “dust” area, and click apply.
  • Hover over the image to review where dust spots were removed. You may optionally click any circle to delete it if the fix causes artifacts or other unwanted results.
  • Use the manual healing brush to remove any spots which were not removed automatically by the AI.
  • Close ACR and if you used it as a filter, you may use a black mask to brush on the smart filter mask to protect any areas from potential unwanted changes (such as the change in the tree and distant hills in the video above).

The new AI Dust removal is an early release feature, which means that it is not yet available in Lightroom – and that it is likely to improve even further.

Add a person to landscapes with Photoshop “harmonize”

Ever wish you had a person in your landscape to show scale? Or wish that you could easily add something new to your photos but it was too hard to match colors and blend the edges? Photoshop’s new “harmonize” feature is designed to let you easily composite anything into your photos and it’s very impressive.

In this tutorial, we’ll add a person to this landscape to give it a sense of scale and make it more interesting. Ideally, I would have a photo of myself or a friend to use – but I haven’t done these sorts of blends in the past because they’re complicated and would have taken a lot of time. So instead, we’ll create someone using the “generate image” AI tool in Photoshop.

The workflow to add a subject and blend with harmonize is:

  • Add a layer with an image of a person – or go to Edit / Generate Image to create one.
    • In the Properties panel, click “remove background” (if you generated the image, right click it to see this option).
    • Resize and position the layer as desired. Click <cmd/ctrl>-T to transform, and right click there if you need advanced options (such as flipping the layer horizontally).
  • Go to Image / Harmonize (you can right-click the layer for this option sometimes).
    • Hide the source layer (PS should do this for you, you don’t want both the old and new showing).
    • With the harmonized layer still selected, go to the Properties panel to select different variations or generate more.
    • Review the result and paint black on the mask if it affects the background, and consider clipping additional adjustments to the layer as needed to refine further.

A few interesting things to note about “harmonize”:

  • The resolution is pretty good and will work great for social media. However, it isn’t yet suitable for full resolution work intended for print.
  • The new harmonize layer covers the entire image. It will show great detail in the original subject pixels, and much lower quality in the areas outside that. The extra pixels allow some blending into the background.

Gain maps vs Tone mapping HDR

One of the most common mistakes photographers make when sharing HDR is to ignore how your image will look on someone else’s monitor. It’s easy to manage once you understand you should always export HDR images with a “gain map (even when encoding as AVIF).

The image below is encoded two different ways, the left side is a simple HDR image (has no gain map). The right side has a gain map. When you view them on a highly capable HDR monitor (one with 4 stops of headroom), they will look nearly identical. Which means you probably wouldn’t notice the difference on the monitor you use to edit HDR.

However, if you view them on a less capable monitor, the gain map on the right will look MUCH better:

  • The AVIF with a gain map (right side) will look great on any display – even if it only supports SDR or has limited HDR.
  • The simple AVIF (left side) will show a number of different issues and varies by browser:
    • in Chrome, the image shows a loss of contrast and detail, unexpected boosts in saturation, and a result that looks almost fake. 
    • in Safari, the tone mapped results are quite different. The sand loses detail, the edges of clouds look flat / unnatural, and there is a significant increase in saturation (even if you like the color boost this is a bad result as it does not match the result I intended as the creator). 
    • in FireFox, the image on the left will look almost black. This shows the backwards compatibility of gain maps.
    • The gain map result on the right is superior in all browsers. While the Safari tone map is better than Chrome on this image, the reverse is often true. It varies by browser, and the automatic tone mapping is nearly always visibly inferior to an image with a gain map created by a photographer.
  • Note: The buttons below the image may be used to limit HDR (assuming you have a supporting HDR display).
    • The red SDR only button will show the SDR result (0 headroom). This button is active by default on this post, so you’ll need to click the other buttons to see HDR in this example.
    • The green button will show the best possible result on your display. If you have 4 stops of headroom, both versions of the image will look the same. This highlights why the value of gain maps isn’t obvious to many creators – the problem shows up on other people’s displays when they don’t have as much HDR support as you!
    • The yellow “limited HDR” button is not supported yet on all browsers and may look the same as the default (full HDR). On Chrome, it seems to limit headroom to 1 stop. This helps to show that gain maps not only improve results for SDR, but also on HDR monitors (anything with less headroom than the image requires).  
simple AVIF => low-quality SDR AVIF with gain map => best SDR

The key lesson here is that gain maps are critical for best results, even with 10+ bit depth formats that natively support HDR (the image on the left is a 10-bit AVIF).

There is a common misperception that the purpose of gain maps is just to add HDR support for the 8-bit JPG format. They serve a much more important role – they ensure your HDR image looks great on any display less capable than yours (higher bit depth does nothing help browser adapt the image). 

To learn more about how gain map work, see great HDR requires a great SDR base image and gain maps make HDR look great on any screen.

To summarize:

  • Always export your HDR images with a gain map (even when using AVIF, JXL, etc) to ensure they look great on any display.
  • A simple HDR image (with no gain map) will almost always look great on your display because you have a great monitor and likely did not edit beyond its capabilities. But this simple image will often look inferior on less capable monitors, and will definitely not be consistent with the version you would print.

If you want to take full control of your gain map to get the best possible result, see the various HDR workflows for exporting via Web Sharp Pro. All of them ensure you control the base SDR in the image for an optimal result on any display. 

For a much deeper discussion of gain maps vs tone maps, please see:

Exposure blend 32-bit photos with luminosity masks

Exposure blending with luminosity masks is one of the most powerful techniques for extracting maximum color and detail from your RAW files. It isn’t just limited to 8 or 16-bits for SDR (“standard dynamic range”) images. You can also blend in 32-bit Photoshop to get the most out of your  32-bit HDR (“high dynamic range”) images, as shown in this tutorial. This allow much more precise masking than is possible in the RAW editing environment alone.

See the final post on my Instagram account in the iPhone or Android app to view as HDR.

The full workflow is:

  • Edit your RAW image in LR or ACR. See here for a deeper dive into the RAW processing.
  • By using virtual copies or a duplicate of your RAW, you can edit it multiple times so that you can optimize separately for the sky and foreground – without making compromises necessary to do both in a single RAW edit.
  • Open the RAW edits as layers in Photoshop. From Lightroom, right-click and choose Edit In / Open as Smart Object layers.
  • Click “PreBlend” in Lumenzia. This is an optional tool for speed – you can manually sort your layers and add black masks to prepare for blending.
  • Use Lumenzia to create a luminosity selection – you will paint white through this selection to reveal each blended layer.
    • There are many potential approaches depending on what you’re doing. See these exposure blending videos for more examples, or my Exposure Blending Master Course to truly understand how to choose ideal selections, manage halos, etc.
    • In this tutorial, I clicked “D” for a darks preview, selected the sky and inverted to isolate the foreground, clicked “Sel” to convert the preview to a luminosity selection, and then double-clicked the – button to create a subtracted selection (see here for more on channel math).
    • Note that you will need Lumenzia v11 or later for 32-bit work (v11.8.10 adds some helpful improvements, so the latest is best).
  • Paint with a white brush (through the luminosity selection) onto the black mask.

After blending, Web Sharp Pro was used to export the HDR for Instagram using HDR workflow #2.

Greg Benz Photography