Our Luminosity Patch Detection test is closely related to our overall Video Dynamic Range test. Dynamic range is the difference between the brightest and darkest parts of an image that a camera can capture. While our Video Dynamic Range test measures the total stops of dynamic range a camera can capture, the Luminosity Patch Detection test measures how much of that dynamic range is allocated above and below middle gray. In other words, how much of a camera's dynamic range is in the highlights vs. the shadows. While this is highly dependent on how you expose your shots—that is, what part of the image you define as middle gray through metering—this test gives you some idea of how many stops you'll get at different luminosities across a camera's ISO range.
We added this test as part of our 0.13 test bench update, along with the related Video Dynamic Range test. For more information, see the test bench 0.13 changelog and the related R&D article, Maximizing A Camera's Video Dynamic Range: Sensitivity Vs. Specificity, A Choice With No Right Answers.
We had no equivalent test prior to test bench 0.13, so any cameras tested on 0.12 or earlier versions won't have these results.
0.8-0.12 | 0.13 | |
---|---|---|
Above Middle Gray | ❌ | ✅ |
Below Middle Gray | ❌ | ✅ |
Learn more about how our test benches and scoring system works.
The goal of the Luminosity Patch Detection test is to ascertain how a camera's dynamic range is allocated in the highlights and shadows of a scene at different ISO settings.
This test is a companion to our Video Dynamic Range measurements and is most valuable taken in the context of that test. Since we don't adjust a camera's exposure during the Luminosity Patch Detection test, it's most useful as a general indicator of how well a camera can capture shadow detail vs highlight detail at different ISO settings. In practice, this will depend greatly on how you expose for a particular scene. Still, knowing how many stops you'll have below middle gray vs. above middle gray can help you expose in a way that either protects more highlights from clipping or reduces noise in the shadows. Striking a balance between the two is optimal in most cases, but this can vary drastically depending on what kind of video you're shooting.
The setup for this test is identical to the Video Dynamic Range test. We shoot the camera on a tripod and use an illuminated Imatest 36-Patch Dynamic Range Test Chart with a DarkWorld Mask in a light-controlled room to eliminate as much ambient light as possible.
Like the Video Dynamic Range test, we record 3-second clips at each ISO setting, starting with a baseline exposure at the camera's base ISO. Where this test diverges, however, is that the exposure—that is, the shutter speed and aperture—is not adjusted as the ISO is raised. We do this primarily to isolate ISO as a variable.
Once the clips have been acquired, we use the same ROI sets captured during the Video Dynamic Range test to run a Python script that analyzes the clips using Fiji and Octave to get our Luminosity Patch Detection data.
We then create a chart to visually represent the data:
Once the chart is created, we take the max number of stops detected in the highlights and note this as our value for Above Middle Gray. Likewise, we input the highest number of stops detected in the shadows from the chart as our value for Below Middle Gray.
Exposure and metering are key here. If you want to protect highlights from clipping, you can underexpose to some degree to prevent the lighter parts of the scene from blowing out at the expense of noisier shadows. On the flip side, overexposing will clip some highlights but retain more detail in the shadows by allowing a greater signal-to-noise ratio (SNR). Knowing how to set your ISO is crucial here, as adjusting the gain will shift what parts of the scene fall above and below middle gray. In general, it's better to get the exposure right in-camera, with less adjustment needed in post, than it is to over or underexpose and then shift things around in post. Shooting in a Log format will allow your camera to capture a wider dynamic range and give you more flexibility to make adjustments after the fact.
Do you have any questions or suggestions concerning our methodology? Are you interested in specific details about our setup, process, or the philosophy behind our tests? We'd love to hear from you in the comments below. You can also email us at feedback@rtings.com.