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Google Pixel 7 Selfie test

OTHER AVAILABLE TESTS FOR THIS DEVICE

We put the Google Pixel 7  through our rigorous DXOMARK Selfie test suite to measure its performance in photo and  video from an end-user perspective. This article breaks down how the device fared in a variety of tests and several common use cases and is intended to highlight the most important results of our testing with an extract of the captured data.

Overview

Key front camera specifications:

  • 10.8MP sensor
  • 1.22µm pixels
  • f/2.2-aperture lens
  • 4K video at 30/60 fps (4K at 30 fps tested)

Scoring

Sub-scores and attributes included in the calculations of the global score.


Google Pixel 7
138
selfie
134
Photo
92

97

105

106

83

103

53

79

79

94

89

91

88

93

65

80

144
Video
81

87

87

90

86

92

72

97

67

83

86

92

82

Best

Pros

  • Natural skin tones and nice white balance, even in difficult conditions
  • Good exposure and wide dynamic range
  • Effective video stabilization
  • Fairly wide depth of field
  • Fairly low noise levels in bright light and indoor conditions

Cons

  • Slight loss of fine detail
  • Out-of-focus faces at close shooting distance
  • Image noise in low light

In our tests, the Google Pixel 7 delivered a very good front camera performance, offering identical results to the flagship Pixel 7 Pro in terms of color and exposure, and getting very close in many other test areas. There were some noteworthy differences between the two devices as well, though.

The focus, which was a point of criticism in our Pixel 7 Pro test, was at close range slightly worse on our Pixel 7 test unit. As a result, textures were not quite as well rendered on the 7 as they were on the 7 Pro, for both Photo and Video. Our testers also saw noticeable differences in the bokeh mode. Unlike the Pro model, the Pixel 7 did not apply a blur gradient to the front of the scene (between camera and subject), which resulted in a lower bokeh score.

In video mode, some artifacts, for example ghosting, were a little more visible on the Pixel 7. These minor differences aside, the Google Pixel 7 still delivered a very reliable front camera performance and is among the best options for passionate selfie shooters.

Google Pixel 7 Selfie Scores vs High-End
This graph compares overall photo and video DXOMARK Selfie scores between tested devices and references. Average and maximum scores of the price segment are also indicated. Average and maximum scores for each price segment are computed based on the DXOMARK database of devices.

Test summary

About DXOMARK Selfie tests: For scoring and analysis, DXOMARK engineers capture and evaluate more than 1,500 test images both in controlled lab environments and in outdoor, indoor and low-light natural scenes, using the front camera’s default settings. The photo protocol is designed to take into account the user’s needs and is based on typical shooting scenarios, such as close-up and group selfies. The evaluation is performed by visually inspecting images against a reference of natural scenes, and by running objective measurements on images of charts captured in the lab under different lighting conditions from 1 to 1,000+ lux and color temperatures from 2,300K to 6,500K. For more information about the DXOMARK Selfie test protocol, click here. More details on how we score smartphone cameras are available here. The following section gathers key elements of DXOMARK’s exhaustive tests and analyses .Full performance evaluations are available upon request. Please contact us on how to receive a full report.

Photo

134

Google Pixel 7

147

Huawei Mate 50 Pro
Google Pixel 7 Photo scores vs High-End
The photo tests analyze image quality attributes such as exposure, color, texture, and noise in various light conditions. Range of focus and the presence of artifacts on all images captured in controlled lab conditions and in real-life images are also evaluated. All these attributes have a significant impact on the final quality of the images captured with the tested device and can help to understand the camera's main strengths and weaknesses.

Exposure

92

Google Pixel 7

97

Apple iPhone 15 Pro

Color

105

Google Pixel 7

106

Google Pixel 8 Pro

Exposure and color are the key attributes for technically good pictures. For exposure, the main attribute evaluated is the brightness of the face(s) in various use cases and light conditions. Other factors evaluated are the contrast and the dynamic range, eg. the ability to render visible details in both bright and dark areas of the image. Repeatability is also important because it demonstrates the camera's ability to provide the same rendering when shooting consecutive images in a row.
For color, the image quality attributes analyzed are skin-tone rendering, white balance, color shading, and repeatability.

Google Pixel 7 – accurate exposure and color
Google Pixel 7 Pro – accurate exposure and color

Focus

83

Google Pixel 7

103

Apple iPhone 15 Pro

Autofocus tests evaluate the accuracy of the focus on the subject’s face, the repeatability of an accurate focus, and the depth of field. While a shallow depth of field can be pleasant for a single-subject selfie or close-up shot, it can be problematic in specific conditions such as group selfies; both situations are tested. Focus accuracy is also evaluated in all the real-life images taken, from 30cm to 150cm, and in low light to outdoor conditions.

Google Pixel 7 - depth of field
Google Pixel 7 - slightly out of focus
Google Pixel 7 Pro - depth of field
Google Pixel 7 Pro - slightly better focus

Texture

53

Google Pixel 7

79

Asus ZenFone 7 Pro

Texture tests analyze the level of details and the texture of subjects in the images taken in the lab as well as in real-life scenarios. For natural shots, particular attention is paid to the level of details in facial features, such as the eyes. Objective measurements are performed on chart images taken in various lighting conditions from 1 to 1000 lux and different kinds of dynamic range conditions. The charts used are the proprietary DXOMARK chart (DMC) and the Dead Leaves chart.

Texture acutance evolution with the illuminance level
This graph shows the evolution of texture acutance with the level of lux for two holding conditions. The texture acutance is measured on the Dead Leaves chart in the Close-up Dead Leaves setup.
Google Pixel 7
Google Pixel 7 - level of detail is slightly lower
Google Pixel 7 Pro detail
Google Pixel 7 Pro - good detail

Noise

79

Google Pixel 7

94

Huawei Mate 50 Pro

Noise tests analyze various attributes of noise such as intensity, chromaticity, grain, and structure on real-life images as well as images of charts taken in the lab. For natural images, particular attention is paid to the noise on faces, but also on dark areas and high dynamic range conditions. Objective measurements are performed on images of charts taken in various conditions from 1 to 1000 lux and different kinds of dynamic range conditions. The chart used is the DXOMARK Dead Leaves chart and the standardized measurement such as Visual Noise derived from ISO 15739.

Visual noise evolution with illuminance levels in handheld condition
This graph shows the evolution of visual noise metric with the level of lux in handheld condition. The visual noise metric is the mean of visual noise measurement on all patches of the Dead Leaves chart in the Close-up Dead Leaves setup. DXOMARK visual noise measurement is derived from ISO15739 standard.

Artifacts

89

Google Pixel 7

91

Apple iPhone 15 Pro

The artifacts evaluation looks at lens shading, chromatic aberrations, distortion measurement on the Dot chart and MTF, and ringing measurements on the SFR chart in the lab. Particular attention is paid to ghosting, quantization, halos, and hue shifts on the face among others. The more severe and the more frequent the artifact, the higher the point deduction on the score. The main artifacts observed and corresponding point loss are listed below.

Main photo artifacts penalties

Bokeh

65

Google Pixel 7

80

Apple iPhone 15 Pro

Bokeh is tested in one dedicated mode, usually portrait or aperture mode, and analyzed by visually inspecting all the images captured in the lab and in natural conditions. The goal is to reproduce portrait photography comparable to one taken with a DSLR and a wide aperture. The main image quality attributes paid attention to are depth estimation, artifacts, blur gradient, and the shape of the bokeh blur spotlights. Portrait image quality attributes (exposure, color, texture) are also taken into account.

Google Pixel 7 – no blur gradient
Google Pixel 7 Pro – blur gradient
Apple iPhone 14 Pro – blur gradient

Video

144

Google Pixel 7

156

Apple iPhone 15 Pro
About DXOMARK Selfie Video tests

DXOMARK engineers capture and evaluate more than 2 hours of video in controlled lab environments and in natural low-light, indoor and outdoor scenes, using the front camera’s default settings. The evaluation consists of visually inspecting natural videos taken in various conditions and running objective measurements on videos of charts recorded in the lab under different conditions from 1 to 1000+ lux and color temperatures from 2,300K to 6,500K.

Google Pixel 7 Video scores vs High-End
Video tests analyze the same image quality attributes as for still images, such as exposure, color, texture, or noise, in addition to temporal aspects such as speed, smoothness, and stability of exposure, white balance, and autofocus transitions.

Exposure

81

Google Pixel 7

87

Apple iPhone 15 Pro

Color

87

Google Pixel 7

90

Apple iPhone 15 Pro

Exposure tests evaluate the brightness of the face and the dynamic range, eg. the ability to render visible details in both bright and dark areas of the image. Stability and temporal adaption of the exposure are also analyzed. Image-quality color analysis looks at skin-tone rendering, white balance, color shading, stability of the white balance and its adaption when light is changing.

Texture

72

Google Pixel 7

97

Asus ZenFone 6

Texture tests analyze the level of details and texture of the real-life videos as well as the videos of charts recorded in the lab. Natural video recordings are visually evaluated, with particular attention paid to the level of detail on the facial features. Objective measurements are performed of images of charts taken in various conditions from 1 to 1000 lux. The chart used is the Dead Leaves chart.

Texture acutance evolution with the illuminance level
This graph shows the evolution of texture acutance with the level of lux for two holding conditions. The texture acutance is measured on the Dead Leaves chart in the Close-up Dead Leaves setup.

Noise

67

Google Pixel 7

83

Xiaomi Mi 11 Ultra

Noise tests analyze various attributes of noise such as intensity, chromaticity, grain, structure, temporal aspects on real-life video recording as well as videos of charts taken in the lab. Natural videos are visually evaluated, with particular attention paid to the noise on faces. Objective measurements are performed on the videos of charts recorded in various conditions from 1 to 1000 lux. The chart used is the DXOMARK visual noise chart.

Spatial visual noise evolution with the illuminance level
This graph shows the evolution of spatial visual noise with the level of lux. Spatial visual noise is measured on the visual noise chart in the video noise setup. DXOMARK visual noise measurement is derived from ISO15739 standard.
Temporal visual noise evolution with the illuminance level
This graph shows the evolution of temporal visual noise with the level of lux. Temporal visual noise is measured on the visual noise chart in the video noise setup.

Stabilization

82

Google Pixel 7

Best

Stabilization evaluation tests the ability of the device to stabilize footage thanks to software or hardware technologies such as OIS, EIS, or any others means. The evaluation looks at overall residual motion on the face and the background, smoothness and jellow artifacts, during walk and paning use cases in various lighting conditions. The video below is an extract from one of the tested scenes.

Artifacts

86

Google Pixel 7

92

Apple iPhone 12 mini

Artifacts are evaluated with MTF and ringing measurements on the SFR chart in the lab as well as frame-rate measurements using the LED Universal Timer. Natural videos are visually evaluated by paying particular attention to artifacts such as quantization, hue shift, and face-rendering artifacts among others. The more severe and the more frequent the artifact, the higher the point deduction from the score. The main artifacts and corresponding point loss are listed below

Main video artifacts penalties

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