In this paper, we propose to study the influence of using head-mounted displays (HMDs) for visual quality rating of omnidirectional images and their impact on the final quality scores. Because of the used display technology, these devices introduce a significant impairment called screen door effect that may alter the quality of experience. Furthermore, the extended use of such a technology may produce cyber-sickness. In this study, a subjective experiment is designed and carried out using various HMDs with various types of content. The statistically analysed results revealed a significant difference between HMDs for quality rating tasks on the overall ratings as well as per individual distortions. These findings will contribute to the development of a reliable protocol for omnidirectional subjective quality assessment, and the constructed database will be used as a ground-truth for quality metrics development.
The camera tuning process contains multiple stages under the image signal processing (ISP) pipeline through which the RAW image gets processed and displayed. The objective image quality is well defined and important when tuning the color imaging pipeline in the Camera. The ISP pipeline is tuned by optimizing objective criteria, resulting image and video may not be aesthetically appealing to end-users and may not be sufficient to provide the best visual experience. There are certain key artistic factors affecting the overall user experience in the process of ISP pipeline tuning. However, currently there is no industry standard for artistic image quality (IQ) quantification and is mostly based on expert based subjective evaluation. In this paper, we emphasize the importance of artistic attributes and to quantify them with two studies. First study focusses on importance of artistic attribute by two alternate forced choice pairwise comparison user study on artistic vs objective tuning. Based on this study, artistic tuning is statistically significantly better than objective tuning with 95% confidence interval based on fisher least significant difference test. Second study develop a method to quantify holistic IQ. The novel mathematical equation has been formulated to calculate the weight of different IQ attributes which are impacting on overall IQ as a first step. Rank based user study was performed on expert and nonexpert users to find their preference on different attributes with the use of novel mathematical equation. In this equation, user preferences were converted into weights of artistic attributes in the holistic IQ. The study shows that color saturation and memory color attributes have higher impact for both expert and non-expert user with weightage of 14.04% and 13.62% in holistic IQ, respectively. This study validates the importance of the artistic approach and our first step to quantify these artistic attributes in a scientific way. It also exhibits the need of a novel image quality assessment criteria to tune and validate the final visual experience of the consumer camera. Especially, in the era of Artificial Intelligence (AI), quantifying artistic attributes is far more important than ever.
Image signal processors (ISP) plays a significant role in camera systems by converting the RAW image from image sensor to a processed image. In order to achieve best image quality, the ISP parameters have to be configured in an iterative manner for various lighting conditions and scenarios, which is carried out by a camera tuning engineer. Usually, the manual tuning process takes up to several weeks to months due to huge number of ISP parameters to be optimized and the iterations involved to achieve good image quality. In this paper, we present a novel approach to automatically tune ISP parameters based on a multi-stage multi-criteria optimization approach using Non sorted Genetic algorithm (NSGA-II) for achieving objective and subjective image quality. In this approach, we focus on important blocks in ISP such as noise reduction, sharpness and tone mapping for human vision use-cases for camera systems widely used for smart phones or smart home IoT devices. The experiments for validating our approach are carried out under different scenarios using Qualcomm’s Spectra 380 ISP simulator and OV13880 sensor and the performance of automatic tuned IQ is compared with manual tuned IQ and some of the previous works done for automatically tuning ISP parameters. With the automatic ISP tuning approach, we verify the significant performance improvement in terms of IQ metrics and time consumed for the tuning process when compared to manual tuning approach.
Nowadays, mobile phone set makers are implementing a full screen display by changing the mounting form factor of the front camera, which is superior in design. When it comes to smart phone front-facing cameras, the hole type front-facing camera degrade the industrial design, while pop-up style camera has also limitation in terms of waterproofness and durability. In the case of Under Display Camera(UDC) which is in its final form factor by design, where a camera is placed underneath the screen, the display panel on the light-receiving path degrades the camera optical sensitivity and causes decrease in image quality performance due to regular display panel pattern. In order to commercialize the UDC, improving image quality of the UDC and exact measurement are crucial. However, subjectively evaluating image taken through the display panel is challenging task measure the image quality performance. This paper introduces a numeric based UDC image quantitative measurement method as a more objective evaluation way.
VCX or Valued Camera eXperience is a nonprofit organization dedicated to the objective and transparent evaluation of mobile phone cameras. The members continuously work on the development of a test scheme that can provide an objective score for the camera performance. Every device is tested for a variety of image quality factors while these typically based on existing standards. Tests include texture loss, resolution, low light performance, shooting time lag, image stabilisation performance and more, all for a variety of different capture conditions. This paper presents that latest development with the newly released version 2020 and the process behind it.
Recently, with the release of 108 mega pixel resolution image sensor, the photo quality of smartphone camera, including detail, and texture, is getting much higher. This became possible only because by utilizing the remosaic technology which re-organize color filter arrays into the Bayer patterns compatible to existing Image Signal Processor (ISP) of commodity AP. However, the optimized parameter configurations of the remosaic block require lots of efforts and long tuning period in order to secure the desired image quality level and sensor characteristics. This paper proposes a deep neural network based camera auto-tuning system for the remosaic ISP block. Firstly, considering the learning phase, big image quality database is created in the random way using reference image and tuning register. Second, the virtual ISP model has been trained in order that predicts image quality by changing sensor tuning registers. Finally, the optimization layer generates the sensor remosaic parameters in order to achieve the user’s target image quality expectation. By experiment, the proposed system has been verified to secure the image quality at the level of professionally hand-tuned photography. Especially, the remosaic artifact of false color, color desaturation and line broken artifacts are improved significantly by more than 23%, 4%, and 12%, respectively.
Smartphone cameras revolutionized for at least two generations in the past decade; i.e. megapixel enthusiasm and multi-camera combination. However, most laptops are still with low resolution fixed focused webcam cameras. The story could have changed recently. The COVID-19 pandemic keeps people working from home; therefore, video conferencing becomes part of the new normal of daily life. The camera quality of laptop computers is in the spotlight when users join video conferences using their laptops webcam. We are working on a MIPI camera solution to drive the Chromebook webcam quality with minimum impact of cost. There are several challenges by porting the current smartphone MIPI camera technology to Chromebook directly: miniature module size and challenge of the hardware product design, limited ISP. There is also no complete evaluation criterion to video conferencing quality. We will discuss each aspect one by one.
Flare, or stray light, is a visual phenomenon generally considered undesirable in photography that leads to a reduction of the image quality. In this article, we present an objective metric for quantifying the amount of flare of the lens of a camera module. This includes hardware and software tools to measure the spread of the stray light in the image. A novel measurement setup has been developed to generate flare images in a reproducible way via a bright light source, close in apparent size and color temperature to the sun, both within and outside the field of view of the device. The proposed measurement works on RAW images to characterize and measure the optical phenomenon without being affected by any non-linear processing that the device might implement.
Several years ago, the geometric calibration of cameras based on diffractive optical elements was invented, and since October 2020 the first product is commercially available.A laser beam is expanded, and the plane wave falls onto a diffractive optical element. The DOE generates a regular grid of light dots that virtually originates from infinity.This structure is then captured with the device under test and the dot positions are detected. From the positions, the required values can be calculated.The potential of the method, the compactness of the setup and the ease of use have brought up many desires that so far had not been addressed.Amongst these are: <list list-type="order"> <list-item>Calibration of extreme wide field of view cameras > 140°.</list-item> <list-item>Calibration of cameras/lens combinations with a large entrance pupil.</list-item> <list-item>Increased camera DOE distance to, e.g., measure cameras behind a windshield in automotive applications.</list-item> <list-item>Camera pairs with a stereo base significantly exceeding 60 mm.</list-item> <list-item>Deriving the point spread function of the system at every light dot to use the method for more than just distortion measurement, e.g., MTF determination or visualization.</list-item> </list>There are also a few limitations compared to the conventional methods: <list list-type="lower-alpha"> <list-item>Measurement at infinity only</list-item> <list-item>Stereo basis cannot be measured due to translation invariance of the method</list-item> <list-item>Determination of chromatic aberration</list-item> <list-item>Limited application of a single DOE (due to resolution of the camera and field of view)</list-item> </list>All these desires and limitations are discussed, and solutions are presented where possible.