Honor Magic5 Pro Selfie test

Exposure and color are the key attributes for technically good images. For exposure, the main attribute evaluated is the brightness of faces under various use cases and lighting conditions. Other factors evaluated are contrast and dynamic range, e.g. the ability to make details visible 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.
Regarding color, the image quality attributes analyzed are skin tone rendering, white balance, color shading and repeatability.

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

Texture tests analyze the level of detail and texture of subjects in images taken in the lab and in real-life scenarios. For natural shots, special attention is paid to the level of detail of facial features, such as the eyes. 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 papers used are the proprietary SBMARK (DMC) paper and the Dead Leaves paper.

Noise tests analyze various noise attributes such as intensity, chromaticity, grain and texture on real images and on graph images taken in the laboratory. For natural images, particular attention is paid to noise on faces, but also to dark areas and high dynamic range conditions. Objective measurements are performed on graph images taken under various conditions from 1 to 1000 lux and different types of dynamic range conditions. The graph used is the SBMARK Dead Leaves graph and the standardized measurement such as visual noise derived from ISO 15739.

Artifact evaluation looks at lens shading, chromatic aberrations, distortion measurements on the Dot and MTF graph, and sound measurements on the SFR graph in the lab. Particular attention is paid to ghosting, quantization, halos and tone changes on the face, among others. The more severe and frequent the artifact, the greater the point deduction from the score. The main artifacts observed and the corresponding point loss are listed below.

SBMARK engineers capture and evaluate more than 2 hours of video in controlled laboratory environments and natural low-light scenes, indoors and outdoors, using default front camera settings. The evaluation consists of visual inspection of natural videos taken under various conditions and performing objective measurements on videos of graphs recorded in the laboratory under different conditions from 1 to 1000+ lux and color temperatures from 2,300 K to 6,500 K.

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

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

Noise tests analyze various noise attributes such as intensity, chromaticity, grain, structure, temporal aspects on real video recordings and on videos of graphs taken in the laboratory. Natural videos are evaluated visually, with particular attention to noise on faces. 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.

The stabilization rating checks the device’s ability to stabilize footage thanks to software or hardware technologies such as OIS, EIS or any other means. The evaluation examines overall residual motion on the face and background, smoothness, and yellow artifacts, during walking and panning use cases under various lighting conditions. The video below is an excerpt of one of the scenes tested.

Artifacts are evaluated with MTF and ringing measurements on the SFR graph 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 frequent the artifact, the greater the deduction of points from the score. The main artifacts and the corresponding point loss are listed below