Author Archives: DXOMARK

The classic window pattern with a black background is the basis of any display characterization, but nowadays, displays, particularly smartphone displays, integrate complex image processing and adaptations, meaning that they cannot be entirely characterized with these simple patterns. 

The number of cameras designed for capturing the nearinfrared (NIR) spectrum (sometimes in addition to the visible) is increasing in automotive, mobile, and surveillance applications. Therefore, NIR LED light sources have become increasingly present in our daily lives. Nevertheless, camera evaluation metrics are still mainly focused on sensors in the visible spectrum. 

In this paper, we propose a rating protocol for evaluating smartphone audio zoom systems through objective and perceptual testing. Audio zoom is a newly developed function that helps isolate a sound source from its surroundings in accordance with the smartphone camera’s focal point and zoom level when recording videos with the camera app. 

The wide use of cameras by the public has raised the interest of image quality evaluation and ranking. Current cameras embed complex processing pipelines that adapt strongly to the scene content by implementing, for instance, advanced noise reduction or local adjustment on faces. 

Nowadays, cameras are widely used to detect potential obstacles for driving assistance. The safety challenges have pushed the automotive industry to develop a set of image quality metrics to measure the intrinsic camera performances and degradations. However, more metrics are needed to correctly estimate computer vision algorithms performance, which depends on environmental conditions. 

Year after year, the demand for ever-better smartphone photos continues to grow, in particular in the domain of portrait photography. Manufacturers thus use perceptual quality criteria throughout the development of smartphone cameras. This costly procedure can be partially replaced by automated learning-based methods for image quality assessment (IQA).

High Dynamic Range (HDR) videos attract industry and consumer markets thanks to their ability to reproduce wider color gamuts, higher luminance ranges and contrast. While the cinema and broadcast industries traditionally go through a manual mastering step on calibrated color grading hardware, consumer cameras capable of HDR video capture without user intervention are now available. 

R. Falcon, M. Patti, S. Brochard-Garnier, G. Pacianotto Gouveia, S. Torres Acevedo, T. Bergot, R. Alarcon, C. Bomstein, H. Macudzinski, P. Maitre, L. Chanas, H. Nguyen, B. Pochon, F. Guichard Videoconferencing has become extremely relevant in the world in the past few  years. Traditional image and video quality evaluation techniques prove to be insufficient to […]

Cameras, especially camera phones, are using a large diversity of technologies, such as multi-frame stacking and local tone mapping to capture and render scenes with high dynamic range. ISO-defined charts for OECF estimation and visual noise measurement are not really designed for these specific use cases, especially when no manual control of the camera is […]

We tackle the issue of estimating the noise level of a camera, on its processed still images and as perceived by the user. Commonly, the characterization of the noise level of a camera is done using objective metrics determined on charts containing uniform patches at a given condition.