Earlier this year, DXOMARK introduced its Decodes series, which aims to explain concepts or dispel myths related to technology, particularly in smartphones and other consumer electronics.
As an experienced scientific tester of smartphones, DXOMARK is in a unique position to measure how well a device’s cameras, audio, display, and battery perform through its rigorous protocols that assess the user’s experience. What we see every day is that tuning is the critical step in finding the right balance between software and hardware interaction so that the user can benefit from all of the device’s features. Striking that optimization balance is often an art that involves strategic choices on the part of the phone manufacturer.
Earlier this year we focused on the importance of software tuning to the display experience. In this latest installment of our series, we’ll try to decode how a large main camera sensor affects the image quality of the device’s photos.
Some smartphone makers, such as Honor, Oppo, Vivo, and Xiaomi, have recently touted their use of big sensors, the so-called “1-inch sensor,” in their smartphone cameras. But does a big sensor alone help to improve image quality?
In this article, we’ll touch on some of the advantages as well as the disadvantages of having a large sensor in your smartphone. We’ll also take a look at the shooting scenarios that benefit from a large sensor, which could explain the trend toward larger sensors in smartphone cameras.
First, what we call a 1-inch sensor does not really refer to a sensor that measures 1-inch. The history of the term is linked to the days when video was shot through tubes that measured 1-inch in outside diameter and had a diagonal of 16mm. This number should be read as the equivalent for a 1- inch video camera tube. Manufacturers’ phone specifications often express the sensor sizes as a fraction of a 1-inch video camera tube.
Some manufacturers, however, do not specify the smartphone camera’s sensor size, but if the number of pixels is known as well as the size of the pixels, it is possible to estimate the sensor size. For example, for a camera with 48 MP and pixel size of 1.22 µm, the formula to estimate the sensor size is 48 MP x 1.22 µm x 1.22 µm = 71.44 mm² (sensor area.)
Another thing to keep in mind is that a large sensor does not necessarily mean a higher pixel count, or better resolution. While a large sensor has the space to accommodate more pixels, a small sensor could contain the same amount of pixels as a large sensor. What could affect image quality would be the size of the pixels on the sensor. And that’s a company’s strategic choice between the desired resolution and image quality, because the smaller the pixel, the lower the signal-to-noise ratio, and therefore the lower resulting quality.
Over the past years, smartphone manufacturers have been increasing the size of the sensor to improve the sensitivity to light.
For example, Apple has doubled the size of the light-sensitive surface between the iPhone 12 Pro Max and iPhone 15 Pro Max, which corresponds to a gain of one stop. If we look at the flagship smartphone cameras released in 2023, the Oppo Find X6 Pro also has double the area compared to the iPhone 15 Pro Max, which corresponds also to one stop.
Main benefits of a large sensor
Many smartphone users often express their frustration with their low-light pictures and videos. A key area for improvement for all smartphone cameras continues to be low-light performance.
In the days of film photography, the only option for photographers to combat low-light challenges was to extend the capture time. But they faced the risk of generating motion blur if the subject was moving or if the photographer was holding the camera. In digital photography, the answer to combating low-light challenges is found in reaching a good balance between texture (detail) and noise. Small sensors often produce a lower texture/noise ratio in the final images. Big sensors are a great tool to improve this ratio.
Low-light photography and videography are where we generally see the biggest gap in quality between small sensors and big sensors. Big sensors have a larger surface exposed to light, allowing them to capture more photons. More photons mean more signal, even in low light. Hence, all things being equal, increasing the size of the sensor enables better low-light performance. Night photography is a situation where having a large sensor can help with image quality.
The following examples are a photographer’s renderings of night scenes.
On the other hand, while a big sensor paired with a lens with a large aperture could be ideal for portraits and low-light images, it might not be ideal for photos where a large depth of field is needed, such as landscape photography or group portraits.
Modern smartphones use bright lenses, with an aperture often under f/2.0. This, in combination with big sensors, produces a shallow depth of field, which is the range of distance in which a person or an object is in focus. The deeper the depth of field, the easier it is for the phone to find the right focus plan. This might affect autofocus stability.
Beyond the specs
There are clever ways to optimize a device to get better image results. Tuning is the art of making the best out of all the image-processing algorithms available. These algorithms are found in the Image Signal Processing (ISP) chip or the camera app code. It is very much like cooking: It requires many tries and fails to find the perfect recipe. There is one recipe for each type of scene.
There are several levers that camera makers can use to optimize image results. Among the top ones:
- Increase the sensor size: This directly increases the photon flow and thus the signal-to-noise ratio. The sensor sizes among the flagships released in 2023 are within a range of one stop. As we saw, the drawback of larger sensors is a smaller depth of field.
- Increase lens aperture. This is characterized by a low f-number. It directly increases the photon flow and thus the signal-to-noise ratio. As of today, all smartphones already have a very large aperture (small f-number). A large aperture also comes with the drawback of a smaller depth of field.
- Use optical image stabilization (OIS): Thanks to OIS, it is possible to compensate for hand motions, which allows for a higher exposure time, and therefore higher signal-to-noise ratio. The OIS offers a potential gain between 0 and 2 stops (in other words, quadrupling the exposure time without motion blur due to hand shake). On the downside, it comes with motion blur, when motion is present in the scene.
- Integrate computational photography solutions, such as image fusion: This solution uses information from several frames, which increases the signal-to-noise ratio, just like a higher exposure time. For example, in order to limit motion blur, the camera could reconstruct an image with sharp detail and low noise by shooting several frames at a short exposure time instead of taking one single long exposure time frame. The potential drawback is an artifact called “ghosting,” which can be visible in the image if several of the frames are not merged properly, especially if there is motion in the scene. The best smartphones today use up to roughly a dozen frames, which corresponds to a potential gain of more than 3 stops!
- Improve denoising algorithms: This solution consists of designing complex image processing algorithms to digitally clean the signal from the noise. Over the past 20 years, huge improvements have been made in this area, making this solution the largest provider of virtual gain in sensitivity. Of course, all this depends on the tuning to control the potential side effects. Indeed, strong denoising can come at the cost of reducing the level of details in the image or introducing unpleasant artifacts.
Can tuning make the difference?
Having great hardware helps with the tuning because it transmits better information to the camera app. For big sensors, the signal is better for noise and texture. But its shallow depth of field makes it harder to tune the autofocus. Tuning teams therefore face contradictory objectives. Will they put more effort into focus performance or texture/noise ratio?
For example, attempting to improve both texture and noise in low-light conditions is particularly challenging because they usually work against each other.
Let’s look at the effect of tuning and sensor size on low-light performance. To do so, we selected ultra-premium (>800€) smartphones launched since 2022. The key image quality attributes are texture and noise. Here, we narrowed the analysis to the scores in low-light conditions.
We observed that small sensors, in general, present a limit in terms of texture and noise score compromise. On the graph below, which includes the scores of some of the best devices from 2022 to 2023, it can go as high as 104 points for the noise score and 97 points for the texture score.
Big sensors on the other hand, can beat these numbers both for texture and noise. To date, two 1-inch sensor smartphones are the best devices in low light. They reached the two top spots in both low-light texture and noise categories under our DXOMARK Camera v5 test protocol. However, using a big sensor does not remove the necessity of putting some efforts into algorithms and tuning. We see that because some other devices with large sensors are low in both texture and noise, with scores under 80.
Big sensors in smartphone cameras can provide some significant advantages in some situations such as low-light photography. But they are not the only answer. Smart and properly tuned software can sometimes compensate for a smaller sensor. All things being equal, a big sensor comes with challenges for other situations such as depth of field management. Proper tuning is essential more than ever if a device is to fully benefit from its performant hardware. So when it comes to image quality, a bigger sensor is not always better!
Be sure to follow all the latest camera test results on dxomark.com.