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Author Archives: DXOMARK
Scientific Publications
From faces to HDR scenes objective and perceptual metrics for AI smart glasses image quality
Apr
Artificial Intelligence (AI) smart glasses with integrated cameras are becoming increasingly prevalent, yet their image quality remains underexplored. This study presents a comprehensive evaluation protocol tailored for such human-facing wearable devices, using both standardized and proprietary metrics (including AI based metrics). Key metrics include Local Contrast Gain (LCG), face exposure, texture preservation, visual noise in […]
Apr
Samsung has introduced the next generation of its flagship smartphone, the Samsung Galaxy S26 Ultra. The device is positioned as an evolution of its predecessor, bringing a series of refinements rather than a complete redesign. While the hardware updates remain relatively limited, Samsung highlights improvements in software processing and image optimization. At DXOMARK, the smartphone […]
Apr
Image stabilization is key to capturing sharp photos and smooth videos, especially in low light or handheld conditions. Modern devices rely on several stabilization technologies: Each system has its strengths and limitations, and its performance can vary greatly depending on the situation. While the CIPA DC-X011 standard defines how photo stabilization should be evaluated for […]
Tech Article
Stab series : How to Create and Use Realistic Movements for Stabilization Testing? (3/3)
Apr
Accurately evaluating image stabilization requires reproducing how people truly use and therefore shake their devices. At DXOMARK, this process begins with capturing real-world user motions using a professional-grade orientation sensor that fuses data from the gyroscope, accelerometer, and magnetometer. Using internal processing, these signals provide a stable, accurate, and continuous estimation of the device’s angular […]
Apr
This work provides a novel glass-to-glass metric of local contrast, useful in the context of image quality evaluation of HDR content. This metric, called Local-Contrast Gain (LCG), uses the opto-optical transfer function (OOTF) of the imaging system and its first derivative to compute the incremental ratio between contrast in the scene and contrast on the […]
Scientific Publications
Analysis of a new HDR dataset of laboratory scenes images using the ICtCp color space
Apr
This paper is the continuation of a previous work in [1], which aimed to develop a color rendering model using ICtCp color space, to evaluate SDR and HDR-encoded content. However, the model was only tested on an SDR image dataset. The focus of this paper is to provide an analysis of a new HDR dataset […]
Scientific Publications
Objective color characterization of HDR videos captured by smartphones: Laboratory setups an analysis framework
Apr
A. Tigranyan, P. Mathieu, C. Nannini, F. Thomas, M. Patti, F. Guichard This article provides elements to answer the question: How to judge general stylistic color rendering choices made by imaging devices capable of recording HDR formats in an objective manner? The goal of our work is to build a framework to analyze color rendering […]
Apr
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).