Visual Comfort Assessment for Stereoscopic Image Retargeting

In recent years, visual comfort assessment (VCA) for 3D/stereoscopic content has aroused extensive attention. However, much less work has been done on the perceptual evaluation of stereoscopic image retargeting. In this paper, we first build a Stereoscopic Image Retargeting Database (SIRD), which contains source images and retargeted images produced by four typical stereoscopic retargeting methods. Then, the subjective experiment is conducted to assess four aspects of visual distortion, i.e. visual comfort, image quality, depth quality and the overall quality. Furthermore, we propose a Visual Comfort Assessment metric for Stereoscopic Image Retargeting (VCA-SIR). Based on the characteristics of stereoscopic retargeted images, the proposed model introduces novel features like disparity range, boundary disparity as well as disparity intensity distribution into the assessment model. Experimental results demonstrate that VCA-SIR can achieve high consistency with subjective perception

Objective Evaluation Criteria for Shooting Quality of Stereo Cameras over Short Distance

Stereo cameras are the basic tools used to obtain stereoscopic image pairs, which can lead to truly great image quality. However, some inappropriate shooting conditions may cause discomfort while viewing stereo images. It is therefore considerably necessary to establish the perceptual criteria that can be used to evaluate the shooting quality of stereo cameras. This article proposes objective quality evaluation criteria based on the characteristics of parallel and toed-in camera configurations. Considering the different internal structures and basic shooting principles, this paper focuses on short-distance shooting conditions and establishes assessment criteria for both parallel and toed-in camera configurations. Experimental results show that the proposed evaluation criteria can predict the visual perception of stereoscopic images and effectively evaluate stereoscopic image quality

An improved model of binocular energy calculation for full-reference stereoscopic image quality assessment

With the exponential growth of stereoscopic imaging in various applications, it has become very demanding to have a reliable quality assessment technique to measure the human perception of stereoscopic images. Quality assessment of stereoscopic visual content in the presence of artefacts caused by compression and transmission is a key component of end-to-end 3D media delivery systems. Despite a few recent attempts to develop stereoscopic image/video quality metrics, there is still a lack of a robust stereoscopic image quality metric. Towards addressing this issue, this paper proposes a full reference stereoscopic image quality metric, which mimics the human perception while viewing stereoscopic images. A signal processing model that is consistent with physiological literature is developed in the paper to simulate the behaviour of simple and complex cells of the primary visual cortex in the Human Visual System (HVS). The model is trained with two publicly available stereoscopic image databases to match the perceptual judgement of impaired stereoscopic images. The experimental results demonstrate a significant improvement in prediction performance as compared with several state-of-the-art stereoscopic image quality metrics

Stereoscopic Omnidirectional Image Quality Assessment Based on Predictive Coding Theory

Objective quality assessment of stereoscopic omnidirectional images is a challenging problem since it is influenced by multiple aspects such as projection deformation, field of view (FoV) range, binocular vision, visual comfort, etc. Existing studies show that classic 2D or 3D image quality assessment (IQA) metrics are not able to perform well for stereoscopic omnidirectional images. However, very few research works have focused on evaluating the perceptual visual quality of omnidirectional images, especially for stereoscopic omnidirectional images. In this paper, based on the predictive coding theory of the human vision system (HVS), we propose a stereoscopic omnidirectional image quality evaluator (SOIQE) to cope with the characteristics of 3D 360-degree images. Two modules are involved in SOIQE: predictive coding theory based binocular rivalry module and multi-view fusion module. In the binocular rivalry module, we introduce predictive coding theory to simulate the competition between high-level patterns and calculate the similarity and rivalry dominance to obtain the quality scores of viewport images. Moreover, we develop the multi-view fusion module to aggregate the quality scores of viewport images with the help of both content weight and location weight. The proposed SOIQE is a parametric model without necessary of regression learning, which ensures its interpretability and generalization performance. Experimental results on our published stereoscopic omnidirectional image quality assessment database (SOLID) demonstrate that our proposed SOIQE method outperforms state-of-the-art metrics. Furthermore, we also verify the effectiveness of each proposed module on both public stereoscopic image datasets and panoramic image datasets

Using disparity for quality assessment of stereoscopic images

International audience3DTV has been widely studied these last years from a technical point of view but the related quality evaluations does not follow this enthusiasm. This article reviews the quality assessment for 3DTV. Compared to 2D quality measure, the third dimension adds several new problems and quality assessment becomes a complex issue. Nevertheless, efforts made for 2D content quality estimation can be used for an extension to 3D. In this paper we propose a first attempt to adapt such 2D metrics to 3D content and add the contribution of a measure of the distortion on the disparity map for stereoscopic image pairs. This 3D metric performances has been evaluated with subjective tests

Stereoscopic image quality assessment method based on binocular combination saliency model

The objective quality assessment of stereoscopic images plays an important role in three-dimensional (3D) technologies. In this paper, we propose an effective method to evaluate the quality of stereoscopic images that are afflicted by symmetric distortions. The major technical contribution of this paper is that the binocular combination behaviours and human 3D visual saliency characteristics are both considered. In particular, a new 3D saliency map is developed, which not only greatly reduces the computational complexity by avoiding calculation of the depth information, but also assigns appropriate weights to the image contents. Experimental results indicate that the proposed metric not only significantly outperforms conventional 2D quality metrics, but also achieves higher performance than the existing 3D quality assessment models

CYCLOP: A stereo color image quality assessment metric

International audienceIn this work, a reduced reference (RR) perceptual quality metric for color stereoscopic images is presented. Given a reference stereo pair of images and their "distorted" version, we first compute the disparity map of both the reference and the distorted stereoscopic images. To this end, we define a method for color image disparity estimation based on the structure tensors properties and eigenvalues/eigenvectors analysis. Then, we compute the cyclopean images of both the reference and the distorted pairs. Thereafter, we apply a multispectral wavelet decomposition to the two cyclopean color images in order to describe the different channels in the human visual system (HVS). Then, contrast sensitivity function (CSF) filtering is performed to obtain the same visual sensitivity information within the original and the distorted cyclopean images. Thereafter, based on the properties of the human visual system (HVS), rational sensitivity thresholding is performed to obtain the sensitivity coefficients of the cyclopean images. Finally, RR stereo color image quality assessment (SCIQA) is performed by comparing the sensitivity coefficients of the cyclopean images and studying the coherence between the disparity maps of the reference and the distorted pairs. Experiments performed on color stereoscopic images indicate that the objective scores obtained by the proposed metric agree well with the subjective assessment scores