Influence of chroma variations on naturalness and image quality of stereoscopic images

The computational view on image quality of Janssen and Blommaert states that the quality of an image is determined by the degree to which the image is both useful (discriminability) and natural (identifiability). This theory is tested by creating two manipulations. Firstly, multiplication of the chroma values of each pixel with a constant in the CIELab color space, i.e., chroma manipulation, is expected to increase only the usefulness by increasing the distances between the individual color points, enhancing the contrast. Secondly, introducing stereoscopic depth by varying the screen disparity, i.e., depth manipulation, is expected to increase both the usefulness and the naturalness. Twenty participants assessed perceived image quality, perceived naturalness and perceived depth of the manipulated versions of two natural scenes. The results revealed a small, yet significant shift between image quality and naturalness as a function of the chroma manipulation. In line with previous research, preference in quality was shifted to higher chroma values in comparison to preference in naturalness. Introducing depth enhanced the naturalness scores, however, in contrast to our expectations, not the image quality scores. It is argued that image quality is not sufficient to evaluate the full experience of 3D. Image quality appears to be only one of the attributes underlying the naturalness of stereoscopic images

Influence of chroma variations on naturalness and image quality of stereoscopic images

The computational view on image quality of Janssen and Blommaert states that the quality of an image is determined by the degree to which the image is both useful (discriminability) and natural (identifiability). This theory is tested by creating two manipulations. Firstly, multiplication of the chroma values of each pixel with a constant in the CIELab color space, i.e., chroma manipulation, is expected to increase only the usefulness by increasing the distances between the individual color points, enhancing the contrast. Secondly, introducing stereoscopic depth by varying the screen disparity, i.e., depth manipulation, is expected to increase both the usefulness and the naturalness. Twenty participants assessed perceived image quality, perceived naturalness and perceived depth of the manipulated versions of two natural scenes. The results revealed a small, yet significant shift between image quality and naturalness as a function of the chroma manipulation. In line with previous research, preference in quality was shifted to higher chroma values in comparison to preference in naturalness. Introducing depth enhanced the naturalness scores, however, in contrast to our expectations, not the image quality scores. It is argued that image quality is not sufficient to evaluate the full experience of 3D. Image quality appears to be only one of the attributes underlying the naturalness of stereoscopic images

Influence of chroma variations on naturalness and image quality of stereoscopic images

The computational view on image quality of Janssen and Blommaert states that the quality of an image is determined by the degree to which the image is both useful (discriminability) and natural (identifiability). This theory is tested by creating two manipulations. Firstly, multiplication of the chroma values of each pixel with a constant in the CIELab color space, i.e., chroma manipulation, is expected to increase only the usefulness by increasing the distances between the individual color points, enhancing the contrast. Secondly, introducing stereoscopic depth by varying the screen disparity, i.e., depth manipulation, is expected to increase both the usefulness and the naturalness. Twenty participants assessed perceived image quality, perceived naturalness and perceived depth of the manipulated versions of two natural scenes. The results revealed a small, yet significant shift between image quality and naturalness as a function of the chroma manipulation. In line with previous research, preference in quality was shifted to higher chroma values in comparison to preference in naturalness. Introducing depth enhanced the naturalness scores, however, in contrast to our expectations, not the image quality scores. It is argued that image quality is not sufficient to evaluate the full experience of 3D. Image quality appears to be only one of the attributes underlying the naturalness of stereoscopic images.Man-Machine InteractionElectrical Engineering, Mathematics and Computer Scienc

Impact of Imaging and Distance Perception in VR Immersive Visual Experience

Virtual reality (VR) headsets have evolved to include unprecedented viewing quality. Meanwhile, they have become lightweight, wireless, and low-cost, which has opened to new applications and a much wider audience. VR headsets can now provide users with greater understanding of events and accuracy of observation, making decision-making faster and more effective. However, the spread of immersive technologies has shown a slow take-up, with the adoption of virtual reality limited to a few applications, typically related to entertainment. This reluctance appears to be due to the often-necessary change of operating paradigm and some scepticism towards the "VR advantage". The need therefore arises to evaluate the contribution that a VR system can make to user performance, for example to monitoring and decision-making. This will help system designers understand when immersive technologies can be proposed to replace or complement standard display systems such as a desktop monitor. In parallel to the VR headsets evolution there has been that of 360 cameras, which are now capable to instantly acquire photographs and videos in stereoscopic 3D (S3D) modality, with very high resolutions. 360° images are innately suited to VR headsets, where the captured view can be observed and explored through the natural rotation of the head. Acquired views can even be experienced and navigated from the inside as they are captured. The combination of omnidirectional images and VR headsets has opened to a new way of creating immersive visual representations. We call it: photo-based VR. This represents a new methodology that combines traditional model-based rendering with high-quality omnidirectional texture-mapping. Photo-based VR is particularly suitable for applications related to remote visits and realistic scene reconstruction, useful for monitoring and surveillance systems, control panels and operator training. The presented PhD study investigates the potential of photo-based VR representations. It starts by evaluating the role of immersion and user’s performance in today's graphical visual experience, to then use it as a reference to develop and evaluate new photo-based VR solutions. With the current literature on photo-based VR experience and associated user performance being very limited, this study builds new knowledge from the proposed assessments. We conduct five user studies on a few representative applications examining how visual representations can be affected by system factors (camera and display related) and how it can influence human factors (such as realism, presence, and emotions). Particular attention is paid to realistic depth perception, to support which we develop target solutions for photo-based VR. They are intended to provide users with a correct perception of space dimension and objects size. We call it: true-dimensional visualization. The presented work contributes to unexplored fields including photo-based VR and true-dimensional visualization, offering immersive system designers a thorough comprehension of the benefits, potential, and type of applications in which these new methods can make the difference. This thesis manuscript and its findings have been partly presented in scientific publications. In particular, five conference papers on Springer and the IEEE symposia, [1], [2], [3], [4], [5], and one journal article in an IEEE periodical [6], have been published