A NEW OBJECTIVE STEREOSCOPIC IMAGE ASSESSMENT MODEL BASED ON STEREOSCOPIC PERCEPTION

In order to establish a stereoscopic image quality assessment method which is consistent with human visual perception,we propose an objective stereoscopic image quality assessment method.It takes into account the strong correlation and high degree of structural between pixels of image.This method contains two models.One is the quality synthetic assessment of left-right view images,which is based on human visual characteristics,we use the Singular Value Decomposition(SVD)that can represent the degree of the distortion,and combine the qualities of left and right images by the characteristics of binocular superposition.The other model is stereoscopic perception quality assessment,due to strong stability of image’s singular value characteristics,we calculate the distance of the singular values and structural characteristic similarity of the absolute difference maps,and utilize the statistical value of the global error to evaluate stereoscopic perception.Finally,we combine two models to describe the stereoscopic image quality.Experimental results show that the correlation coefficients of the proposed assessment method and the human subjective perception are above 0.93,and the mean square errors are all less than 6.2,under JPEG,JP2K compression,Gaussian blurring,Gaussian white noise,H.264 coding distortion,and hybrid cross distortion.It indicates that the proposed stereoscopic objective method is consistent with human visual properties and also of availability.

AB019. A proposed test of stereovision to identify local retinal abnormalities

Background:The human visual system extracts depth information from disparity in the images seen by the two eyes.The ability to calculate depth from disparity will be disrupted if local retinal abnormalities distort parts of those images,especially if these distortions are different in the two eyes.In its early stages,age-related macular degeneration(AMD)causes slight distortions in the central vision field which differ in the two eyes.AMD is the most common form of irreversible blindness in people over the age of 50.The goal of this project is to develop a stereoscopic perception test which leverages the sensitivity of binocular depth perception to detect the interocular differences symptomatic of either early-stage AMD or other diseases affecting the retina.Methods:A program was written in MATLAB that allowed separate left and right eye stimuli to be shown to the two eyes.NVIDIA 3D Vision 2 stereoscopic glasses were used to present the stimuli.The test we have developed consists of random dot patterns covering the central 5 degrees of vision.One or more disk-shaped perturbations in depth are displayed at different locations in the visual field of the subjects.Of the ten possible target locations,we present between one and four disks on each trial.The disks will only be visible if there is an undistorted input for that visual field location from the two retinae.The participant uses a keypad to report the number of floating disks seen.A set of trials with randomized locations and numbers of disks is used to gather initial data on likely areas of stereoscopic vision deficit;afterwards,likelihoods for deficits in each location are calculated and used to generate customized subsequent trials.Results:The software to perform the local stereovision test has been developed and is now being piloted.We are currently collecting data from healthy normal subjects prior to applying the test to clinical populations.In order to simulate the central vision distortions of AMD,patches of the stimulus for one eye are scrambled and blurred.This allows us to ensure that the task is functioning correctly.Conclusions:The next step for this project is for it to be tested on ageing clinical populations to find its effectiveness in differentiating patients with normal sight from those showing early symptoms of AMD or other retinal abnormalities such as diabetic retinopathy.This test could represent a novel approach in early clinical detection of ocular disease.