Spatio-temporal Contrast Sensitivity Function Research Articles

Spatio-temporal generalized Model Observers methods for Low Contrast Detectability assessment in digital angiography: Application to moving targets

The purpose of this work is to investigate the feasibility of spatio-temporal generalized Model Observer methods for protocol optimization programs in the field of interventional radiography.Two Model Observers were taken under examination: a Channelized Hotelling Observer with 24 spatio-temporal Gabor channels and a Non Pre-Whitening Model Observer with two different implementations of the spatio-temporal contrast sensitivity function. The images of targets, both stationary and in motion, were acquired in fluoroscopic mode using a CDRAD phantom for signal-present images and an homogenous slab of PMMA for signal-absent ones.After the processing, these images were used to build three series of two alternative forced choice experiments, designed to simulate tasks of clinical interest, and submitted to three human observers in order to set a goal on detectability. A first set of images was used for model tuning and subsequently the verified models were validated throughout a second set of images.Results from the validation phase, for both models, show good agreement with the human observer performances (Root Mean Square Error RMSE ≤ 12%).The tuning phase emerges as a crucial step in building models for angiographic dynamic images; the final agreement underlines the good capability of these spatio-temporal models in simulating human performances, allowing to consider them as a useful and worthwhile tool in protocol optimization when dynamic images are involved.

Spatiotemporal Contrast Sensitivity of Brown-Norway Rats under Scotopic and Photopic Illumination

Rats are a popular animal model for vision research and for investigating disorders of the visual system. The study aimed to quantify the spatiotemporal contrast sensitivity function (CSF) of healthy adult Brown-Norway rats under scotopic and photopic illumination. Animals were trained to jump onto the one of two adjacent platforms behind which was displayed a sinewave grating pattern. Contrast thresholds of light- and dark-adapted rats were determined using a staircase method of adjustment for gratings that varied in spatial frequency (sf) and temporal frequency (tf) and ranged several log-units in mean luminance. Photopic CSFs showed strong bandpass spatial tuning, consistent with prior measurements, and weak bandpass temporal tuning. CSFs were parameterized by a truncated log-parabola model, yielding a peak contrast sensitivity of 52 ± 9, peak sf of 0.17 ± 0.05 cycles/degree, sf limit of 1.6 ± 0.3 cycles/degree, low sf attenuation of 85 ± 9%, peak tf of 1.7 ± 1.1 Hz, extrapolated tf limit of 166 ± 44 Hz, and low tf attenuation of 55 ± 12%. CSFs became more lowpass and decreased systematically in contrast sensitivity and spatiotemporal acuity as mean luminance was reduced. CSFs were also measured via the visual head-tracking reflex. Photopic contrast sensitivity, spatial acuity, and temporal acuity were all markedly below that of the grating detection task and optomotor findings for other rat strains. The CSF data provide a comprehensive and quantitative description of rat spatial and temporal vision and a benchmark for evaluating effects of ocular diseases on their ability to see.

Predicting visible flicker in temporally changing images

Novel display algorithms such as low-persistence displays, black frame insertion, and temporal resolution multiplexing introduce temporal change into images at 40-180 Hz, on the boundary of the temporal integration of the visual system. This can lead to flicker, a highly-objectionable artifact known to induce viewer discomfort. The critical flicker frequency (CFF) alone does not model this phenomenon well, as flicker sensitivity varies with contrast, and spatial frequency; a content-aware model is required. In this paper, we introduce a visual model for predicting flicker visibility in temporally changing images. The model performs a multi-scale analysis on the difference between consecutive frames, normalizing values with the spatio-temporal contrast sensitivity function as approximated by the pyramid of visibility. The output of the model is a 2D detection probability map. We ran a subjective flicker marking experiment to fit the model parameters, then analyze the difference between two display algorithms, black frame insertion and temporal resolution multiplexing, to demonstrate the application of our model.

54. Spatio-temporal generalisation of Model Observer for Low Contrast Detectability assessment of dynamic angiographic images: comparison with an innovative Statistical method and 2AFC experiments

Purpose Evaluate the feasibility of different less time consuming approaches for protocol optimisation in interventional radiology. Methods A Allura FD20 (Philips, The Netherlands) has been employed in this study. Low Dose Fluoroscopy was selected due to its spatial resolution, characterised by a lower enhancement compared to other modalities. Simulated images have been obtained adding a blurred circular insert to a series of acquired homogeneous images. A total of 3 insert dimensions (1.25, 2, 3 mm of diameter), 25 contrast levels and 4 different visualised frame rate (5, 10, 15 and 30 fps) have been selected to characterise low contrast detectability. A series of 2AFC experiments have been performed by two observers. Two different Model Observers has been considered: Non-PreWhitening Eye filter (NPWE) with spatio-temporal contrast sensitivity function and Channelized Hotelling Observer (CHO) with spatio-temporal Gabor filters. Furthermore, Low Contrast Detectability has been evaluated with a statistical method using uniform images. This analysis has been performed on an averaging of frames depending from the visualised fps. In particular, the averaging process was performed on groups of frames that correspond to the noise integration time of human eye-brain system of 200 ms, e.g. 3 frames with 15 fps. Results Analysis with both Model Observers and 2AFC experiments suffered from the general low quality of the protocol considered (Fig. 1). Nevertheless, a good agreement ( Conclusions The agreement with human observer experiments underlines the feasibility of the proposed generalisations. Thus, they could be introduced for a deeper modalities characterisation, in terms of image quality, or for clinical protocol optimization involving cine images.

OA096] Low contrast detectability assessment of dynamic angiographic images: spatio-temporal generalisation of model observer and comparison with 2AFC experiments

Purpose Evaluate the feasibility of spatio-temporal generalisation of mathematical approaches for protocol optimisation in interventional radiology. Methods A Allura FD20 (Philips, The Netherlands) has been employed in this study. Two different Model Observers has been considered: Non-PreWhitening Eye filter (NPWE) with spatio-temporal contrast sensitivity function and Channelized Hotelling Observer (CHO) with spatio-temporal Gabor filters. Furthermore, Low Contrast Detectability has been evaluated with a statistical method using uniform images. This analysis has been performed on an averaging of frames depending from the visualised fps. In particular, the averaging process was performed on groups of frames that correspond to the noise integration time of human eye-brain system of 200 ms, e.g. 3 frames with 15 fps. A series of 2AFC experiments have been performed by two observers. The evaluation and characterization of the mathematical approaches were performed throughout two different phases: firstly, a series of simulated images of the insert were used to characterize the models. A total of 3 insert dimensions (1.25, 2, 3 mm of diameter), 25 contrast levels and 4 different visualised frame rate (5, 10, 15 and 30 fps) have been selected to characterise low contrast detectability. Results of this analysis were than used to evaluate low contrast detectability with the acquired images of a dedicated commercial phantom CDRAD phantom (Artinis Medical Systems, The Netherlands). Four modalities were selected in this study. A total of 3 insert dimensions (1.3, 2, 3.2 mm of diameter), 15 contrast levels have been selected for every considered modality. Results Analyses with simulated images underline a good agreement ( Conclusions The agreement with human observer experiments underlines the feasibility of the proposed generalisations. Thus, they could be introduced for a deeper modalities characterisation, in terms of image quality, or for clinical protocol optimization involving cine images.

Cube-based perceptual weighted Kronecker Compressive Sensing: Can we avoid non-visible redundancies acquisition?

Compressive sensing approach directly avoids the acquisition of statistical redundancies of a signal. However, perceptual redundancies of images and videos due to the human eye sensitivity are not considered so far. Besides, an effective sampling scheme is needed to multidimensional signal reconstruction using a low number of measurements to avoid all redundancies. In this paper, along with the Kronecker structure of the sampling matrix we design various weighting matrices based on the spatio-temporal contrast sensitivity function to avoid acquisition of non-visible redundancies. Moreover, inspired by the block-based compressive sensing, we divide a group of pictures in a video sequence into cubes. Hence, the size of measurement and sparsifying basis matrices are reduced and the reconstruction algorithm can be implemented in parallel. We further show that our simple linear sampling approach can be competitive with motion compensation method. Simulation results verify that our proposed method notably outperforms the other state-of-the-art methods.

Estimating just‐noticeable distortion for images/videos in pixel domain

Existing pixel-based just noticeable distortion (JND) models only take into account luminance adaptation and texture masking (TM). Similarly, existing discrete cosine transform (DCT) based models do not take into account foveal vision effects and do not estimate TM efficiently. As human visual system (HVS) is not sensitive to distortion below the JND threshold, estimation of the perceptual visibility threshold is widely used in digital and video processing applications. The authors propose a comprehensive and efficient pixel-based JND model incorporating all major factors which contribute to the JND estimation. The evaluation of contrast masking (CM) is done by distinguishing the edge and TM with respect to the entropy masking properties of the HVS. Similarly, the foveal vision effects are also taken into account for the comprehensive estimation of contrast sensitivity function (CSF). Hence, the proposed pixel-based JND model incorporates the spatio-temporal CSF, foveal vision effects, influence of eye-movement, luminance adaptation and CM to be more consistent with human perception. The incorporation of these important factors makes the proposed model the most comprehensive and efficient in the current literature. Psychophysical experiments were performed to test the proposed model. The results show the proposed model comprehensively outperforms other existing models proving its efficiency.

Peripheral resolution and contrast sensitivity: Effects of stimulus drift

Optimal temporal modulation of the stimulus can improve foveal contrast sensitivity. This study evaluates the characteristics of the peripheral spatiotemporal contrast sensitivity function in normal-sighted subjects. The purpose is to identify a temporal modulation that can potentially improve the remaining peripheral visual function in subjects with central visual field loss. High contrast resolution cut-off for grating stimuli with four temporal frequencies (0, 5, 10 and 15Hz drift) was first evaluated in the 10° nasal visual field. Resolution contrast sensitivity for all temporal frequencies was then measured at four spatial frequencies between 0.5 cycles per degree (cpd) and the measured stationary cut-off. All measurements were performed with eccentric optical correction. Similar to foveal vision, peripheral contrast sensitivity is highest for a combination of low spatial frequency and 5–10Hz drift. At higher spatial frequencies, there was a decrease in contrast sensitivity with 15Hz drift. Despite this decrease, the resolution cut-off did not vary largely between the different temporal frequencies tested. Additional measurements of contrast sensitivity at 0.5 cpd and resolution cut-off for stationary (0Hz) and 7.5Hz stimuli performed at 10, 15, 20 and 25° in the nasal visual field also showed the same characteristics across eccentricities.

No-Reference Quality Assessment of H.264/AVC Encoded Video

This paper proposes a no-reference quality assessment metric for digital video subject to H.264/advanced video coding encoding. The proposed metric comprises two main steps: coding error estimation and perceptual weighting of this error. Error estimates are computed in the transform domain, assuming that discrete cosine transform (DCT) coefficients are corrupted by quantization noise. The DCT coefficient distributions are modeled using Cauchy or Laplace probability density functions, whose parameterization is performed using the quantized coefficient data and quantization steps. Parameter estimation is based on a maximum-likelihood estimation method combined with linear prediction. The linear prediction scheme takes advantage of the correlation between parameter values at neighbor DCT spatial frequencies. As for the perceptual weighting module, it is based on a spatiotemporal contrast sensitivity function applied to the DCT domain that compensates image plane movement by considering the movements of the human eye, namely smooth pursuit, natural drift, and saccadic movements. The video related inputs for the perceptual model are the motion vectors and the frame rate, which are also extracted from the encoded video. Subjective video quality assessment tests have been carried out in order to validate the results of the metric. A set of 11 video sequences, spanning a wide range of content, have been encoded at different bitrates and the outcome was subject to quality evaluation. Results show that the quality scores computed by the proposed algorithm are well correlated with the mean opinion scores associated to the subjective assessment.

A Video Quality Assessment Metric Based on Human Visual System

It is important for practical application to design an effective and efficient metric for video quality. The most reliable way is by subjective evaluation. Thus, to design an objective metric by simulating human visual system (HVS) is quite reasonable and available. In this paper, the video quality assessment metric based on visual perception is proposed. Three-dimensional wavelet is utilized to decompose video and then extract features to mimic the multichannel structure of HVS. Spatio-temporal contrast sensitivity function (S-T CSF) is employed to weight coefficient obtained by three-dimensional wavelet to simulate nonlinearity feature of the human eyes. Perceptual threshold is exploited to obtain visual sensitive coefficients after S-T CSF filtered. Visual sensitive coefficients are normalized representation and then visual sensitive errors are calculated between reference and distorted video. Finally, temporal perceptual mechanism is applied to count values of video quality for reducing computational cost. Experimental results prove the proposed method outperforms the most existing methods and is comparable to LHS and PVQM.

Estimating Just-Noticeable Distortion for Video

Just-noticeable distortion (JND), which refers to the maximum distortion that the human visual system (HVS) cannot perceive, plays an important role in perceptual image and video processing. In comparison with JND estimation for images, estimation of the JND profile for video needs to take into account the temporal HVS properties in addition to the spatial properties. In this paper, we develop a spatio-temporal model estimating JND in the discrete cosine transform domain. The proposed model incorporates the spatio-temporal contrast sensitivity function, the influence of eye movements, luminance adaptation, and contrast masking to be more consistent with human perception. It is capable of yielding JNDs for both still images and video with significant motion. The experiments conducted in this study have demonstrated that the JND values estimated for video sequences with moving objects by the model are in line with the HVS perception. The accurate JND estimation of the video towards the actual visibility bounds can be translated into resource savings (e.g., for bandwidth/storage or computation) and performance improvement in video coding and other visual processing tasks (such as perceptual quality evaluation, visual signal restoration/enhancement, watermarking, authentication, and error protection)

Visual Warning Signals Optimized for Human Perception: What the Eye Sees Fastest

This study aimed to answer the question of how to design a visual warning signal that is most easily seen and produces the quickest reaction time. This is a classic problem of bionic optimization—if one knows the properties of the receiver one can most easily find a suitable solution. Because the peak of the spatio-temporal contrast sensitivity function of the human visual system occurs at non-zero spatial and temporal frequencies, it is likely that movement enhances the detectability of threshold visual signals. Earlier studies employing extended drifting sinewave gratings bear out this prediction. We have studied the ability of human observers to detect threshold visual signals for both moving and stationary stimuli. We used discrete, localized signals such as might be employed in aerospace or automotive warning signal displays. Moving stimuli show a superior detectability to non-moving stimuli of the same integrated energy. Moving stimuli at threshold detectability are seen faster than non-moving threshold stimuli. Under some conditions the speed advantage is over 0.25 seconds. Similar advantages have also been shown to occur for suprathreshold signals.

Effects of motion blurring in x-ray fluoroscopy

In conventional fluoroscopy, continuous x-ray exposure blurs moving objects, while in pulsed fluoroscopy, short duration x-ray pulses acquire images without motion blur. Many perception experiments on noisy image sequences are consistent with low-pass temporal filtering by the human visual system, and this is anticipated to cause visual system "blurring" of moving objects. With moving cylinders in spatially white noise, we simulated 30 acq/s (acquisitions per second), continuous fluoroscopy having both x-ray and visual system motion blur. We also simulated pulsed fluoroscopy at 30 acq/s (pulsed-30) having visual system but not x-ray system motion blur. For both continuous and pulsed-30 acquisitions, with increasing velocity, detectability of small cylinders decreased by as much as approximately 50%, while detectability of large cylinders increased and then decreased. Detectability of pulsed-30 was only slightly higher than continuous, indicating that visual system motion blurring dominated x-ray system blurring. For the case of stationary objects, blurring greatly reduced detectability, indicating that last-image-hold of moving objects deteriorates with continuous acquisitions. With no free parameters, a human observer model with an independently measured spatio-temporal contrast sensitivity function accurately described all effects.

Detection of moving objects in pulsed-x-ray fluoroscopy.

We investigated the detectability of moving, low-contrast objects in white-noise image sequences. The computer-generated, cylindrical phantoms mimicked arteries, catheters, and guide wires in medical, x-ray fluoroscopy image sequences at 16 acquisitions/s (pulsed-16) or 32 acquisitions/s (pulsed-32). We measured detectability by using a reference-test, adaptive forced-choice method whereby reference and test presentations were alternated during an experimental session to minimize effects of subject attention and accuracy criteria. In the case of the largest cylinder (diameter 0.48 deg), the highest speed (5.86 deg/s) increased absolute detectability by approximately 42% compared with that in the stationary case. With the smallest cylinder (diameter 0.023 deg), this motion decreased detectability by approximately 51%. The dose savings of pulsed-16 was approximately 18% of that for pulsed-32, with relatively little effect of velocity or object size. In general, subjects took slightly longer to respond in the case of low-acquisition fluoroscopy. Detectability data were modeled with a nonprewhitening matched filter that included a physiological, spatiotemporal contrast sensitivity function and a suboptimal, spatiotemporal signal template with time-limited memory.