Rich Structural Index for Stereoscopic Image Quality Assessment

The human visual system (HVS), affected by viewing distance when perceiving the stereo image information, is of great significance to study of stereoscopic image quality assessment. Many methods of stereoscopic image quality assessment do not have comprehensive consideration for human visual perception characteristics. In accordance with this, we propose a Rich Structural Index (RSI) for Stereoscopic Image objective Quality Assessment (SIQA) method based on multi-scale perception characteristics. To begin with, we put the stereo pair into the image pyramid based on Contrast Sensitivity Function (CSF) to obtain sensitive images of different resolution . Then, we obtain local Luminance and Structural Index (LSI) in a locally adaptive manner on gradient maps which consider the luminance masking and contrast masking. At the same time we use Singular Value Decomposition (SVD) to obtain the Sharpness and Intrinsic Structural Index (SISI) to effectively capture the changes introduced in the image (due to distortion). Meanwhile, considering the disparity edge structures, we use gradient cross-mapping algorithm to obtain Depth Texture Structural Index (DTSI). After that, we apply the standard deviation method for the above results to obtain contrast index of reference and distortion components. Finally, for the loss caused by the randomness of the parameters, we use Support Vector Machine Regression based on Genetic Algorithm (GA-SVR) training to obtain the final quality score. We conducted a comprehensive evaluation with state-of-the-art methods on four open databases. The experimental results show that the proposed method has stable performance and strong competitive advantage.

"Interior view of a hut ...": Stereography and the depiction of an Interior Architecture in 1930

This paper is an exploration of a stereographic photograph taken inside a New Zealand backcountry hut. Matter-of-factly entitled, "Interior view of a hut, with mugs, a bottle, plate and cutlery on a table, looking through door to another hut, location unidentified," the photograph is attributed by the Alexander Turnbull Library to keen amateur photographer Edgar Richard Williams. The image gives little detail away in its depiction of the hut interior, except for a utilitarian table tableau that begins to suggest a nascent New Zealand interior defined by no-nonsense pragmaticism and Lea & Perrins. But, far from being a scene of Depression-era poverty and deprivation, close examination of the photographed situation and its broader context provides a glimpse into a monied amateurism that heralded an emergent leisure class. As a stereoscopic image, the photograph does more than depict a scene. By placing us within a spatial view, we become immersed in questions concerning interiority and exteriority. We are presented with two spatial contrasts: one in the subject of the image, the other in the object of the image. By taking a close reading of both contrasts, this paper is an attempt to make some architectural sense of these dualities.

A Benchmark Evaluation of Adaptive Image Compression for Multi Picture Object Stereoscopic Images

A stereopair consists of two pictures related to the same subject taken by two different points of view. Since the two images contain a high amount of redundant information, new compression approaches and data formats are continuously proposed, which aim to reduce the space needed to store a stereoscopic image while preserving its quality. A standard for multi-picture image encoding is represented by the MPO format (Multi-Picture Object). The classic stereoscopic image compression approaches compute a disparity map between the two views, which is stored with one of the two views together with a residual image. An alternative approach, named adaptive stereoscopic image compression, encodes just the two views independently with different quality factors. Then, the redundancy between the two views is exploited to enhance the low quality image. In this paper, the problem of stereoscopic image compression is presented, with a focus on the adaptive stereoscopic compression approach, which allows us to obtain a standardized format of the compressed data. The paper presents a benchmark evaluation on large and standardized datasets including 60 stereopairs that differ by resolution and acquisition technique. The method is evaluated by varying the amount of compression, as well as the matching and optimization methods resulting in 16 different settings. The adaptive approach is also compared with other MPO-compliant methods. The paper also presents an Human Visual System (HVS)-based assessment experiment which involved 116 people in order to verify the perceived quality of the decoded images.