In the above paper (ibid., vol. 22, no. 12, pp. 5146-5157, Dec. 2013), a delay in communicating proof errors occurred. The paper was published without corrections. The corrections presented here are important.

The development of video quality metrics requires methods for measuring perceived video quality. Most of these metrics are designed and tested using databases of images degraded by compression and scored using opinion ratings. We studied video quality preferences for enhanced images of normally-sighted participants using the method of paired comparisons with a thorough statistical analysis. Participants (n=40) made pair-wise comparisons of high definition video clips enhanced at four different levels using a commercially available enhancement device. Perceptual scales were computed with binary logistic regression to estimate preferences for each level and to provide statistical inference of the differences among levels and the impact of other variables. While moderate preference for enhanced videos was found, two unexpected effects were also uncovered: 1) participants could be broadly classified into two groups: a) those who preferred enhancement ("Sharp") and b) those who disliked enhancement ("Smooth") and 2) enhancement preferences depended on video content, particularly for human faces to be enhanced less. The results suggest that algorithms to evaluate image quality (at least for enhancement) may need to be adjusted or applied differentially based on video content and viewer preferences. The possible impact of similar effects on image quality of compressed video needs to be evaluated.

Gaze tracking is crucial for studying driver's attention, detecting fatigue, and improving driver assistance systems, but it is difficult in natural driving environments due to nonuniform and highly variable illumination and large head movements. Traditional calibrations that require subjects to follow calibrators are very cumbersome to be implemented in daily driving situations. A new automatic calibration method, based on a single camera for determining the head orientation and which utilizes the side mirrors, the rear-view mirror, the instrument board, and different zones in the windshield as calibration points, is presented in this paper. Supported by a self-learning algorithm, the system tracks the head and categorizes the head pose in 12 gaze zones based on facial features. The particle filter is used to estimate the head pose to obtain an accurate gaze zone by updating the calibration parameters. Experimental results show that, after several hours of driving, the automatic calibration method without driver's corporation can achieve the same accuracy as a manual calibration method. The mean error of estimated eye gazes was less than 5°in day and night driving.

Virtual reality locomotion simulators are a promising tool for evaluating the effectiveness of vision aids to mobility for people with low vision. This study examined two factors to gain insight into the verisimilitude requirements of the test environment: the effects of treadmill walking and the suitability of using controls as surrogate patients. Ten "tunnel vision" patients with retinitis pigmentosa (RP) were tasked with identifying which side of a clearly visible obstacle their heading through the virtual environment would lead them, and were scored both on accuracy and on their distance from the obstacle when they responded. They were tested both while walking on a treadmill and while standing, as they viewed a scene representing progress through a shopping mall. Control subjects, each wearing a head-mounted field restriction to simulate the vision of a paired patient, were also tested. At wide angles of approach, controls and patients performed with a comparably high degree of accuracy, and made their choices at comparable distances from the obstacle. At narrow angles of approach, patients' accuracy increased when walking, while controls' accuracy decreased. When walking, both patients and controls delayed their decisions until closer to the obstacle. We conclude that a head-mounted field restriction is not sufficient for simulating tunnel vision, but that the improved performance observed for walking compared to standing suggests that a walking interface (such as a treadmill) may be essential for eliciting natural perceptually-guided behavior in virtual reality locomotion simulators.

Virtual environments (VEs) allow safe, repeatable, and controlled evaluations of obstacle avoidance and navigation performance of people with visual impairments using visual aids. Proper simulation of mobility in a VE requires an interface, which allows subjects to set their walking pace. Using conventional treadmills, the subject can change their walking speed by pushing the tread with their feet, while leveraging handrails or ropes (self-propelled mode). We developed a feedback-controlled locomotion interface that allows the VE workstation to control the speed of the treadmill, based on the position of the user. The position and speed information is also used to implement automated safety measures, so that the treadmill can be halted in case of erratic behavior. We compared the feedback-controlled mode to the self-propelled mode by using speed-matching tasks (follow a moving object or match the speed of an independently moving scene) to measure the efficacy of each mode in maintaining constant subject position, subject control of the treadmill, and subject pulse rates. Additionally, we measured the perception of speed in the VE on each mode. The feedback-controlled mode required less physical exertion than self-propelled. The average position of subjects on the feedback-controlled treadmill was always within a centimeter of the desired position. There was a smaller standard deviation in subject position when using the self-propelled mode than when using the feedback-controlled mode, but the difference averaged less than six centimeters across all subjects walking at a constant speed. Although all subjects underestimated the speed of an independently moving scene at higher speeds, their estimates were more accurate when using the feedback-controlled treadmill than the self-propelled.

Subjective evaluation by human observers is usually used to analyze and select an edge detector parametric setup when real-world images are considered. We propose a statistical objective performance analysis and detector parameter selection, using detection results produced by different detector parameters. Using the correspondence between the different detection results, an estimated best edge map, utilized as an estimated ground truth (EGT), is obtained. This is done using both a receiver operating characteristics (ROC) analysis and a Chi-square test, and considers the trade off between information and noisiness in the detection results. The best edge detector parameter set (PS) is then selected by the same statistical approach, using the EGT. Results are demonstrated for several edge detection techniques, and compared to published subjective evaluation results. The method developed here suggests a general tool to assist in practical implementations of parametric edge detectors where an automatic process is required.

An image enhancement algorithm for images compressed using the JPEG standard is presented. The algorithm is based on a contrast measure defined within the discrete cosine transform (DCT) domain. The advantages of the psychophysically motivated algorithm are 1) the algorithm does not affect the compressibility of the original image because it enhances the images in the decompression stage and 2) the approach is characterized by low computational complexity. The proposed algorithm is applicable to any DCT-based image compression standard, such as JPEG, MPEG 2, and H. 261.

An algorithm for the detection of visually relevant luminance features is presented. The algorithm is motivated and directed by current models of the visual system. The algorithm detects edges (sharp luminance transitions) and narrow bars (luminance cusps) and marks them with the proper polarity. The image is first bandpass filtered with oriented filters at a number of scales an octave apart. The suprathreshold image contrast details at each scale are then identified and are compared across scales to find locations in which the signal polarity (sign) is identical at all scales, representing a minimal level of phase congruence across scales. These locations maintain the polarity of the bandpass-filtered image. The result is a polarity-preserving features map representing the edges with pairs of light and dark lines or curves on corresponding sides of the contour. Similarly, bar features are detected and represented with single curves of the proper polarity. The algorithm is implemented without free (fitted) parameters. All parameters are directly derived from visual models and from measurements on human observers. The algorithm is shown to be robust with respect to variations in filter parameters and requires no use of quadrature filters or Hilbert transforms. The possible utility of such an algorithm within the visual system and in computer vision applications is discussed.

Evaluation of retinal images is essential to modern ophthalmic care. With the advent of image processing equipment, digital recording and processing of retinal images is starting to replace the standard film based fundus photography. The ability to enhance images is cited as one of the major benefits of this expensive technology. This paper critically reviews the practices employed in the image enhancement literature. It is argued that the papers published to date have not presented convincing evidence regarding the diagnostic value of retinal image enhancement. The more elaborate studies in radiology suggest, at best, modest diagnostic improvement with enhancement. The special difficulties associated with the demonstration of an improved diagnosis in ophthalmic imaging are discussed in terms of the diagnostic task and the selection of study populations.

Invariant perception of objects is desirable. Contrast constancy assures invariant appearance of suprathreshold image features as they change their distance from the observer. Fully robust size invariance also requires equal contrast thresholds across all spatial frequencies and eccentricities so that near-threshold image features do not appear or disappear with distance changes. This clearly is not the case, since contrast thresholds increase exponentially with eccentricity. We showed that a less stringent constraint actually may be realized. Angular size and eccentricity of image features covary with distance changes. Thus the threshold requirement for invariance could be approximately satisfied if contrast thresholds were to vary as the product of spatial frequency and eccentricity from the fovea. Measurements of observers' orientation discrimination contrast thresholds fit this model well over spatial frequencies of 1 - 16 cycles/degree and for retinal eccentricities up to 23 degrees. Measurements of observers’ contrast detection thresholds from three different studies provided an even better fit to this model over even wider spatial frequency and retinal eccentricity ranges. The fitting variable, die fundamental eccentricity constant, was similar for all three studies (0.036, 0.036, 0.030, respectively). The eccentricity constant for the orientation discrimination thresholds was higher (0.048 and 0.050 for two observers, respectively). We simulated the appearance of images with a nonuniform visual system by applying the proper threshold at each eccentricity and spatial frequency. The images exhibited only small changes over a simulated 4-octave distance range. However, the change in simulated appearance over the same distance range was dramatic for patients with central visual field loss. The changes of appearance across the image as a function of eccentricity were much smaller than in previous simulations, which used data derived from visual cortex anatomy rather than direct measurements of visual function. Our model provides a new tool for analyzing the visibility of displays and for designing equal visibility or various visibility displays.