We subjected the Apple iPhone 14 to our rigorous SBMARK Camera test suite to measure its performance in terms of photo, video and zoom quality from an end-user perspective. This article analyzes how the device performed in a variety of tests and several common use cases and aims to highlight the most important results of our tests with an excerpt of the data captured.

Overview

Main camera specs:

  • Primary: 1/1.9-inch 12MP sensor, 24mm-equivalent f/1.5 aperture lens, Dual PDAF, OIS
  • Ultra Wide: 12MP sensor, 24mm equivalent f/2.4 aperture lens, PDAF

Pros

  • Good exposure and nice color
  • Fast and accurate autofocus
  • Realistic bokeh effect in portrait mode
  • Image preview close to capture
  • Good video exposure and fairly wide dynamic range
  • Very effective video stabilization, even with intense camera shake
  • Good texture/noise compromise in the video
  • Smooth video autofocus with fast convergence

Versus

  • Luminance noise in low light conditions, especially in solid color areas
  • Highlight clipping in heavily backlit scenes
  • Artifacts, including ghosting, ringing, and pitch shifting
  • No macro mode
  • Orange white balance projects in low-light videos
  • Occasional video exposure jitter and slow exposure adjustment
  • Lens flare, ringing and color quantization in video, especially in low light conditions
  • Noise on moving elements in the scene in low light video

Much like the flagship iPhone 14 Pro and 14 Pro Max models, the iPhone 14 proved to be an extremely reliable camera in our tests, producing repeatable image and video results in all conditions. It particularly shined in video, thanks to the high levels of detail, as well as excellent autofocus tracking. However, the camera lagged slightly behind the Pro version in terms of zoom performance. This is mainly due to the lack of a dedicated lens and a small maximum aperture on the ultra wide angle module. With only a 5x digital zoom, the overall zoom capabilities are quite limited, especially at medium to long ranges.

Trial summary

About SBMARK Camera Tests: SBMARK’s camera evaluations are conducted in labs and in real-world situations using a wide variety of subjects. Scores are based on objective tests for which results are calculated directly by the measurement software on our lab setups and perceptual tests where a sophisticated set of metrics allows a panel of image experts to compare aspects of quality of the image that require human judgment. Testing a smartphone involves a team of engineers and technicians for about a week. Photo, zoom, and video quality are rated separately and then combined into an overall score for comparing cameras from different devices. For more information on the SBMARK camera protocol, click here. More details on smartphone camera scores can be found here. The following section compiles the key elements of SBMARK’s exhaustive testing and analysis. Full performance evaluations are available upon request. Please contact us on how to receive a full report.

Camera scores of Apple iPhone 14 vs Premium

This graph compares the SBMARK photo, zoom and video scores between the tested device and the references. The average and maximum scores of the price segment are also indicated. The average and maximum scores for each price segment are calculated based on the SBMARK database of tested devices.

Photo

135

Huawei Mate 50 Pro

Huawei Mate 50 Pro

SBMARK camera photo test information

For scoring and analysis, SBMARK engineers capture and evaluate more than 2,600 test images in both controlled laboratory environments and outdoor, indoor, and low-light natural scenes using camera presets. The photographic protocol is designed to take into account the main use cases and is based on typical shooting scenarios, such as portrait, family and landscape photography. Evaluation is performed by visually inspecting images Cons a natural scene reference and by performing objective measurements on laboratory-acquired graph images under various lighting conditions from 1 to 1,000+ lux and color temperatures from 2,300 K to 6,500 K.

In terms of still image quality, the iPhone 14 was overall pretty close to last year’s 13 Pro and 13 Pro Max, but with improved skin tones in difficult lighting conditions. That said, image noise was slightly more intrusive on the base model iPhone 14 than it was on last year’s 13 Pro models and the latest iPhone 14 Pro.

Apple iPhone 14 photo scores

Photo tests analyze image quality attributes such as exposure, color, texture and noise under various lighting conditions. Autofocus performance and the presence of artifacts are also evaluated on all images acquired under controlled laboratory conditions and on real-life images. All of these attributes have a significant impact on the final quality of the images captured with the tested device and can help you understand the main strengths and weaknesses of the camera.

Exposure

110

Huawei Mate 50 Pro

Huawei Mate 50 Pro

Color

116

Google Pixel 7 Pro

Google Pixel 7 Pro

Exposure and color are key attributes for technically good images. For exposure, the main attribute evaluated is the brightness of the main subject across various use cases such as landscape, portrait or still life. Other factors evaluated are contrast and dynamic range, e.g. the ability to make details visible in light and dark areas of the image. Repeatability is also important because it demonstrates the camera’s ability to provide the same rendering when taking multiple images of the same scene.
For color, the image quality attributes analyzed are skin tone rendering, white balance, color shading, and repeatability. With regards to color rendition and skin tone, we penalize unnatural colors but respect the manufacturer’s choice of color signature.

Apple iPhone 14: White balance cast with less impact on skin tones

Apple iPhone 13 Pro Max: White balance affects skin tones

Google Pixel 7 Pro – almost neutral colors

Auto focus

110

Huawei Mate 50 Pro

Huawei Mate 50 Pro

Autofocus Ruggedness and Speed: 1000Lux Δ0EV Daylight Handheld

This graph illustrates focus accuracy and speed, and also zero shutter lag capability by showing edge acuity versus shooting time measured on the AFHDR setup over a series of images. All photos were taken at 1000 Lux with Daylight illuminant, 500 ms after blurring. Edge sharpness is measured on the four edges of the Dead Leaves graph and shooting time is measured on the Universal Timer LED.

Structure

103

Oppo Find X5

Oppo Find X5

Texture tests analyze the level of detail and texture of subjects in images taken in the lab as well as real-life scenarios. For natural shots, special attention is paid to the level of detail in the light and dark areas of the image. Objective measurements are performed on map images taken under various lighting conditions from 1 to 1000 lux and different types of dynamic range conditions. The charts used are the proprietary SBMARK (DMC) chart and the Dead Leaves chart.

SBMARK CHART (DMC) Detail Retention Score vs. Lux Levels for Tripod and Handheld Conditions

This graph shows the evolution of the DMC Detail Retention score with lux level, for two retention conditions. The DMC Detail Retention Score is derived from an AI-powered metric trained to evaluate texture and detail rendition on a selection of crops from our SBMARK chart.

Noise

80

Honor Magic4 Ultimate

Honor Magic4 Ultimate

Noise tests analyze various noise attributes such as intensity, chromaticity, grain, texture on real-life images and lab-captured graph images. For natural images, special attention is paid to noise on faces, landscapes, but also dark areas and high dynamic range conditions. Noise on moving objects is also evaluated on natural images. Objective measurements are performed on chart images captured under various conditions from 1 to 1000 lux and different types of dynamic range conditions. The graph used is the dead leaves graph and standardized measurement such as visual noise derived from ISO 15739.

Evolution of visual noise with illuminance levels in portable conditions

This graph shows the evolution of the visual noise metric with lux level under palmar conditions. The Visual Noise metric is the average of the Visual Noise measurement across all patches of the Dead Leaves graph in the AFHDR configuration. The SBMARK visual noise measurement is derived from the ISO15739 standard.

Apple iPhone 14 – low light noise

Apple iPhone 14 – very visible noise

Apple iPhone 13 Pro Max – low light noise

Apple iPhone 13 Pro Max – slightly visible noise

Google Pixel 7 Pro – low light noise

Google Pixel 7 Pro: Very well controlled noise

Artifacts

71

Google Pixel 6

Google Pixel 6

Artifact assessment examines lens shading, chromatic aberrations, geometric distortion, ringing edges, halos, ghosting, quantization, unexpected color tone shifts, among other types of possible effects unnatural on photos. The more serious and frequent the artifact, the greater the deduction of points from the score. The main artifacts observed and the corresponding loss of points are listed below.

Major penalties for photographic artifacts

Preview

85

Apple iPhone 14 Pro Max

Apple iPhone 14 Pro Max

The preview tests analyze the image quality of the camera app’s image preview, with particular attention to the difference between the capture and the preview, especially regarding the dynamic range and the application of the bokeh effect. The uniformity of exposure, color and focus adaptation when zooming from the minimum to the maximum available zoom factor is also evaluated. The preview frame rate is measured using the Universal Timer LED.

Apple iPhone 14 preview: exposure and dynamic range quite similar to the capture

Apple iPhone 14 – catch

Zoom in

90

Honor Magic4 Ultimate

Honor Magic4 Ultimate

About SBMARK Camera Zoom Tests

SBMARK engineers capture and evaluate over 400 test images in controlled laboratory environments and natural outdoor, indoor, and low-light scenes using camera presets and pinch zoom at various zoom factors from ultra wide to very long zoom. Evaluation is performed by visually inspecting images Cons a natural scene reference and by performing objective measurements of lab-captured map images under varying conditions from 20 to 1000 lux and color temperatures from 2300K to 6500K.

For a device without a dedicated telephoto lens, the iPhone 14 offered decent enough image quality throughout the zoom range. The ultra-wide results were similar to older iPhone 13 images. The 13mm lens offered a wide field of view and good image quality, but slightly less detail and more noise than the 14 Pro. When using the tele zoom, at close and medium range, the images showed significant improvements over the iPhone 13.

Apple iPhone 14 Zoom scores compared to Premium

This graph illustrates the relative scores for the different zoom ranges evaluated. The abscissa is expressed in focal length equivalent to 35mm. Zoomed scores appear on the right and zoomed scores on the left.

Wide

88

Huawei Mate 50 Pro

Huawei Mate 50 Pro

These tests analyze the performance of the ultra wide angle camera at different focal lengths from 12mm to 20mm. All attributes of image quality are evaluated, with particular attention to artifacts such as chromatic aberrations, lens softness and distortion. The images below are an excerpt from the tested scenes.

Apple iPhone 14 ultra wide – slight loss of detail

Apple iPhone 13 Pro Max ultra wide: better retention of details

Google Pixel 7 Pro ultra wide: better retention of details

tele

60

Honor Magic4 Ultimate

Honor Magic4 Ultimate

All image quality attributes are evaluated at focal lengths from approximately 40mm to 300mm, with an emphasis on texture and detail. The score comes from a series of objective laboratory measurements and perceptual analysis of real-life images.

SBMARK CHART Detail Retention Score (DMC) by focal length

This graph shows the evolution of the DMC Detail Retention score versus the full-frame equivalent focal length for different lighting conditions. The x-axis represents the equivalent focal length measured for each corresponding shooting distance, and the y-axis represents the maximum detail retention metric score: higher value means better quality. Large dots correspond to the zoom ratio available in the camera application UI.

SBMARK CHART Detail Retention Score (DMC) by focal length

This graph shows the evolution of the DMC Detail Retention score versus the full-frame equivalent focal length for different lighting conditions. The x-axis represents the equivalent focal length measured for each corresponding shooting distance, and the y-axis represents the maximum detail retention metric score: higher value means better quality. Large dots correspond to the zoom ratio available in the camera application UI.

SBMARK CHART Detail Retention Score (DMC) by focal length

This graph shows the evolution of the DMC Detail Retention score versus the full-frame equivalent focal length for different lighting conditions. The x-axis represents the equivalent focal length measured for each corresponding shooting distance, and the y-axis represents the maximum detail retention metric score: higher value means better quality. Large dots correspond to the zoom ratio available in the camera application UI.

SBMARK CHART Detail Retention Score (DMC) by focal length

This graph shows the evolution of the DMC Detail Retention score versus the full-frame equivalent focal length for different lighting conditions. The x-axis represents the equivalent focal length measured for each corresponding shooting distance, and the y-axis represents the maximum detail retention metric score: higher value means better quality. Large dots correspond to the zoom ratio available in the camera application UI.

video

146

Apple iPhone 14 Pro Max

Apple iPhone 14 Pro Max

About SBMARK Camera Video Tests

SBMARK engineers capture and evaluate more than 2.5 hours of video in controlled lab environments and low natural light scenes, indoors and out, using the camera’s default settings. Evaluation consists of visually inspecting natural video taken under various conditions and performing objective measurements on lab-recorded graph video under various conditions from 1 to 1000+ lux and color temperatures from 2,300K to 6,500K.

Video tests on the iPhone 14 were performed at 4K resolution and 30 frames per second, with Dolby Vision turned on. The camera delivered excellent video quality overall and showed improvements over the 13 Pro and Pro Max in most video test attributes, getting quite close to the latest iPhone 14 and 14 Pro Max flagships.

Note: YouTube only shows the original HDR rendering if the videos are watched on an HDR compatible display. Otherwise, compressed SDR video is displayed.

Apple iPhone 14 video scores

Video tests analyze the same image quality attributes as still images, such as exposure, color, texture or noise, as well as temporal aspects such as speed, exposure uniformity and stability, white balance and autofocus transitions.

Exposure

114

Apple iPhone 14 Pro Max

Apple iPhone 14 Pro Max

Color

116

Apple iPhone 14 Pro Max

Apple iPhone 14 Pro Max

Exposure tests evaluate the brightness of the main subject and the dynamic range, e.g. the ability to make details visible in light and dark areas of the image. The stability and temporal adaptation of the exposure are also analysed.
Image quality color analysis examines color rendition, skin tone rendition, white balance, color shading, white balance stability and its adaptation when the light changes.

Apple iPhone 14 – precise target exposure, wide dynamic range, pleasant colors

Apple iPhone 13 Pro Max – precise target exposure, wide dynamic range, pleasant colors

Google Pixel 7 Pro – Accurate target exposure, wide dynamic range, saturated colors

Structure

109

Xiaomi Mi 11 Ultra

Xiaomi Mi 11 Ultra

Texture tests analyze the level of detail and texture of real-life videos as well as graphics videos recorded in the lab. Natural video recordings are evaluated visually, with particular attention to the level of detail in bright areas and dark areas. Objective measurements of card images taken under various conditions from 1 to 1000 lux are performed. The charts used are the SBMARK (DMC) chart and the Dead Leaves chart.

SBMARK CHART (DMC) video score for detail retention versus lux levels

This graph shows the evolution of the video DMC detail retention score with the level of lux in the video. The DMC Detail Retention Score is derived from an AI-powered metric trained to evaluate texture and detail rendition on a selection of crops from our SBMARK chart.

Noise

116

Samsung Galaxy A23 5G

Samsung Galaxy A23 5G

Noise tests analyze various noise attributes such as intensity, chromaticity, grain, texture, temporal aspects on real-life video recording, as well as graph videos taken in the lab. Natural videos are evaluated visually, with an emphasis on noise in dark areas and high dynamic range conditions. Objective measurements are performed on graph videos recorded under various conditions from 1 to 1000 lux. The graph used is the SBMARK visual noise graph.

Evolution of spatial visual noise with level of illumination

This graph shows the evolution of spatial visual noise with lux level. Spatial visual noise is measured on the visual noise table in the video noise setup. The SBMARK visual noise measurement is derived from the ISO15739 standard.

Time evolution of visual noise with level of illumination

This graph shows the evolution of visual noise over time with lux level. Temporal visual noise is measured on the visual noise table in the video noise configuration.

Stabilization

116

Apple iPhone 14 Pro Max

Apple iPhone 14 Pro Max

The stabilization rating tests the device’s ability to stabilize footage using software or hardware technologies such as OIS, EIS, or any other means. The evaluation looks at residual motion, smoothness, yellow artifacts, and residual motion blur in walking and running use cases under various lighting conditions. The video below is an excerpt from one of the tested scenes.

Apple iPhone 14: stabilization effective, camera shake still slightly perceptible

Apple iPhone 13 Pro Max: stabilization effective, camera shake still slightly noticeable

Google Pixel 7 Pro: stabilization effective, camera shake still slightly noticeable

Artifacts

73

Xiaomi 12S Ultra

Xiaomi 12S Ultra

Artifacts are evaluated with MTF and ringing measurements on the SFR graph in the lab, as well as frame rate measurements using the Universal Timer LED. Natural videos are visually evaluated by paying close attention to artifacts such as aliasing, quantization, blocking, and pitch shifting, among others. The more severe and frequent the artifact, the more points will be deducted from the score. The main artifacts and the corresponding point loss are listed below.

Top penalties for video artifacts

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Philip Owell

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