Pixel Luminance Research Articles

SeACPFusion: An Adaptive Fusion Network for Infrared and Visible Images based on brightness perception

Generating a single fused image that highlights important targets and preserves textural details is the aim of fusing visible and infrared images. The majority of deep learning-based fusion algorithms now in use can produce decent fusion outcomes; however, the modeling process still lacks consideration of the different amounts of information in different scenes or regions. Thus, we propose in this research SeACPFusion, a luminance-aware adaptive fusion network for infrared and visible images, which adaptively preserves the intensity information of the noticeable targets of the source images with the texture information of the background in an optimal ratio. Specifically, we design pixel-level luminance loss (PBL) to direct the fusion model’s training in real-time, and PBL retains the optimal intensity information according to the pixel luminance ratio of different source images. In addition, we designed the Channel Transformer (CTF) to consider the relationship between different attributes from the point of view of the feature channel and to focus on the key information by using the self-focusing mechanism to achieve the goal of adaptive fusion. Our extensive tests on the MSRS, RoadScene, and TNO datasets demonstrate that SeACPFusion surpasses nine representative deep learning methods on six objective metrics and achieves the best visual results in scenes such as overexposure or underexposure. In addition, the relatively efficient operation and fewer model parameters make our algorithm promising as a preprocessing module for downstream complicated vision tasks.

P‐122: Dependence of Aerial image quality on Display parameters in aerial Display system

In this paper, we report the relationship between the imaging spatial resolution and display parameters of the AIRR (aerial imaging by retro‐reflection) system, which we constructed using displays of different brightness, luminance spatial distribution and pixel pitch, respectively, and a line‐pair MTF‐based measurement method is applied to the system. The MTF measurement results show that the spatial resolution depends on the display pixel period size, luminance intensity and luminance spatial distribution.

Immigration documentation statuses evoke racialized faceism in mental representations

U.S. immigration discourse has spurred interest in characterizing who illegalized immigrants are or perceived to be. What are the associated visual representations of migrant illegality? Across two studies with undergraduate and online samples (N = 686), we used face-based reverse correlation and similarity sorting to capture and compare mental representations of illegalized immigrants, native-born U.S. citizens, and documented immigrants. Documentation statuses evoked racialized imagery. Immigrant representations were dark-skinned and perceived as non-white, while citizen representations were light-skinned, evaluated positively, and perceived as white. Legality further differentiated immigrant representations: documentation conjured trustworthy representations, illegality conjured threatening representations. Participants spontaneously sorted unlabeled faces by documentation status in a spatial arrangement task. Faces’ spatial similarity correlated with their similarity in pixel luminance and “American” ratings, confirming racialized distinctions. Representations of illegalized immigrants were uniquely racialized as dark-skinned un-American threats, reflecting how U.S. imperialism and colorism set conditions of possibility for existing representations of migrant illegalization.

GS-AGC: An Adaptive Glare Suppression Algorithm Based on Regional Brightness Perception

Existing algorithms for enhancing low-light images predominantly focus on the low-light region, which leads to over-enhancement of the glare region, and the high complexity of the algorithm makes it difficult to apply it to embedded devices. In this paper, a GS-AGC algorithm based on regional luminance perception is proposed. The indirect perception of the human eye’s luminance vision was taken into account. All similar luminance pixels that satisfied the luminance region were extracted, and adaptive adjustment processing was performed for the different luminance regions of low-light images. The proposed method was evaluated experimentally on real images, and objective evidence was provided to show that its processing effect surpasses that of other comparable methods. Furthermore, the potential practical value of GS-AGC was highlighted through its effective application in road pedestrian detection and face detection. The algorithm in this paper not only effectively suppressed glare but also achieved the effect of overall image quality enhancement. It can be easily combined with the embedded hardware FPGA for acceleration to improve real-time image processing.

P‐126: An Introduction to GGRB Virtual Pixel Technology

The constructions of the GGRB virtual pixel and the effect on the display performance are introduced by comparing with that of the Diamond RGBG virtual pixel, a typical virtual pixel technology applied to active matrix organic light‐emitting diode (AMOLED) display. Because of the characteristic structure of GGRB sub‐ pixel arrangement, the occurrence of perceptible artificial color discontinuity is reduced in the GGRB virtual pixel display. The distribution uniformity of pixel luminance centroids is important for the display of pattern details. In the GGRB virtual pixel display, the distribution uniformity of pixel luminance centroids is achieved via a non‐uniformly distributed green sub‐pixel array of which the luminance profile is properly modulated by the red and blue sub‐pixels with lower spatial frequency distribution. The results of subjective evaluation and comparison suggest that the performance improvement of the GGRB virtual pixel display is consistent with the conceptual expectation. Some of the essential characteristics is superior to those of the reference technology.

Preview the Products on Display at Display Week 2023

Preview the Products on Display at Display Week 2023

Proposed approximate hybrid memory architecture for handheld multimedia devices

Nowadays Handheld multimedia devices demand is growing rapidly, as the demand for mobility in work and lifestyle increases. Power consumption has become the paramount concern in the design of Handheld multimedia battery-operated devices. Approximate computing promises energy efficiency computing paradigms when small quality degradation is permissible. Most multimedia processing is image or video processing, where the end user is a human. The imperceptibility of the human visual system is to allow the output of this processing to be approximate rather than accurate. This research paper proposed an energy-efficient Moving Picture Experts Group 4 (MPEG-4) video decoder architecture with a circuit-level approximate method for Handhandle multimedia devices. Hence, in this research work instead of using conventional 6T memory cells during video decoding processing, an approximate Hybrid 6T/8T memory architecture is proposed, where the 8-bit Luminance pixels are stored favourably in consonance with their effect on the output quality. The higher order luminance bits (MSBs) require high stability and thus these bits are stored in the 8T bit cells and the remaining bits (LSBs) are stored in the conventional 6T bit cells for more optimal configurations compared with previous work. The failure probability of 6T cells is significantly large 0.0988 at 600 mV supply voltage (as compared to 0.28*10^-2 at 800 mV supply voltage), leading to a decrease in the output quality of the decoded video. The hybrid memory matrix formulation calculates that storing higher-order MSB bits in highly stable memory cells will provide high-quality video processing compared to the conventional technique because the human eye is more susceptible to higher-order luminance bits. The proposed approximate 6T/8T hybrid memory units, and evaluate them to demonstrate the efficacy of our approach. Simulations result indicate power savings of up to 50% with an insignificant loss in output quality (3.6 dB) when compared to the conventional memory unit. Compared to the hybrid and conventional 6T memory array at 600 mV supply voltage, the worst minimum PSNR is 15.04 dB improved.

MPEG/H256 video encoder with 6T/8T hybrid memory architecture for high quality output at lower supply

The use of Multimedia video content is increased rapidly in the past decade, and most multimedia video content is used by mobile phone users. Multimedia video processing consumes significant power during video compression, and thus low power multimedia video compression is essential for battery operated devices. Moving Picture Experts Group (MPEG) Video encoding is giving a higher compression rate and low bandwidth requirement. Conventional MPEG Video encoding architecture uses the conventional 6T memory cells to store video frames for further compression processing. The failure probability of 6T cells is significantly large (0.0988 at 600 mV supply voltage), leading to a decrease in the output quality of the encoded video. From the hybrid memory matrix formulation, it is calculated that storing higher-order MSB bits in highly stable memory cells will provide high-quality video encoding processing as compared to the conventional technique because the human eye is more susceptible to higher-order luminance bits. Hence, in this research work instant of using conventional 6T memory cells during video encoding processing, a unique Hybrid 6T/8T memory architecture is proposed, where the 8-bit Luminance pixels are stored favourably in consonance with their effect on the output quality. The higher order luminance bits (MSB’s) require high stability and thus these bits are stored in the 8T bit cells and the remaining bits (LSB’s) are stored in the conventional 6T bit cells for high-quality video encoding processing. This research article also proposes a separate memory peripheral circuitry for hybrid memory architecture for video encoding techniques. In addition, this article proposes a unique architecture for parallel video processing with the use of a hybrid pixel memory array. The failure probability of 6T and 8T at the worst failure corner (FS corner for read and SF corner for write) is simulated for 30000 Monte-Carlo simulations points at 45 nm CMOS technology node using CADENCE EDA tool. For the simulation work here, a standard Common Intermediate Format/Quarter Common Intermediate Format (CIF/QCIF) Coastguard video sample is used and for output quality here average PSNR method is used and simulation work is performed using the MATLAB tool.The worst PSNR for conventional 6T memory array and Hybrid memory array at 600 mV supply voltage shows improvement in worst minimum PSNR as 6.43 dB is calculated. 30% less power consumption to conventional memory architecture.

Image sequence decomposition via sigma-delta cellular neural network having coupled cells

In this paper, an image sequence decomposition by the sigma-delta cellular neural network (SD-CNN) with coupled cells and its composition framework is proposed. The SD-CNN, having coupled cells inspired by the second-order sigma-delta modulator, is employed for image sequence decomposition, and it enables effective image decomposition by the effects of complex dynamics. In our method, pixel luminance is described by the number of spikes within a discrete time window that corresponds to the number of SD-CNN iterations. For efficient image decomposition, a high luminance which requires a long time window, should be compensated. To solve this problem, we introduce the cumulated luminance integrator enables compensating a high luminance even with a short time window. Experimental results on various test images in the Kodak dataset and the Waterloo dataset support that all the test images can be mathematically lossless reconstructed from an image sequence decomposed via our method. It is also confirmed that the proposed method improves transmission efficiency for the Kodak dataset by approximately 80%, which is an issue with our previous method.

A Highly Uniform Luminance and Low-Flicker Pixel Circuit and Its Driving Methods for Variable Frame Rate AMOLED Displays

A Highly Uniform Luminance and Low-Flicker Pixel Circuit and Its Driving Methods for Variable Frame Rate AMOLED Displays

An automated method for BRISQUE quantification of image quality in echocardiography

Abstract Background Echocardiography (echo) remains the most widely used imaging modality for the assessment, monitoring, and prognostication of the heart. Despite its prevalence, standardisation efforts for echo chamber quantification are ongoing, with challenges owing to subjectivity during acquisition and analysis. Furthermore, the confidence in derived functional indices is often dependent on the quality of the acquired images. However, few studies have investigated the accuracy of echo measurements compared to a reference modality such as cardiac magnetic resonance (CMR) imaging, when stratified by image quality. Purpose To develop an objective and automated method to quantify echo image quality, and subsequently to investigate the relationship between image quality and patient demographics, as well as the magnitude of bias in left ventricular (LV) functional indices compared with CMR. Methods Transthoracic apical 2D echo (2DE) and 3D echo (3DE) data from 128 participants (72 healthy controls and 56 patients with acquired heart disease) were used to train a BRISQUE (Blind/Referenceless Image Spatial Quality Evaluator) algorithm [1]. Briefly, feature extraction was performed by fitting pixel luminances to a generalised Gaussian distribution (GGD), followed by support vector regression to correlate features (i.e., shape, variance, and mean parameters of the GGD) to quality scores (Fig. 1). Independent BRISQUE models were trained on 580 2DE images (consisting of 2-, 3-, and 4-chamber views) and 128 targeted LV 3DE acquisitions at end-diastole, each assigned a subjective perceived quality score between 1 (poor) and 9 (excellent) by a single observer. LV indices including end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), and global longitudinal strain (GLS), were assessed according to standard guidelines. Resultant BRISQUE scores were plotted against patient demographics (age, height, weight) and the measurement bias by comparison to CMR (acquired within 1 hour of echo). Results Several linear relationships (where P-value of slope <0.05) were observed between demographics, cardiac indices, and BRISQUE scores. Increasing patient weight (and height in 3DE) were found to be associated with poorer image quality. There was no apparent relationship between image quality and age. Of interest, EF exhibited a relationship with image quality in both 2DE and 3DE (Fig. 2), whereby higher quality images tended to overestimate EF, while lower quality images underestimated EF. For 3DE, image quality dependency was also observed for ESV and GLS biases. Conclusions BRISQUE can objectively quantify image quality to produce scores which correlate to those of an expert observer, with potential utility for the standardised quantification of echo image quality. Using this method, it may be possible to predict patient characteristics which adversely impact echo quality, as well as the magnitude of measurement biases for certain functional indices. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Health Research Council (HRC) of New Zealand; National Heart Foundation (NHF) of New Zealand

Color-Perception-Guided Display Power Reduction for Virtual Reality

Battery life is an increasingly urgent challenge for today's untethered VR and AR devices. However, the power efficiency of head-mounted displays is naturally at odds with growing computational requirements driven by better resolution, refresh rate, and dynamic ranges, all of which reduce the sustained usage time of untethered AR/VR devices. For instance, the Oculus Quest 2, under a fully-charged battery, can sustain only 2 to 3 hours of operation time. Prior display power reduction techniques mostly target smartphone displays. Directly applying smartphone display power reduction techniques, however, degrades the visual perception in AR/VR with noticeable artifacts. For instance, the "power-saving mode" on smartphones uniformly lowers the pixel luminance across the display and, as a result, presents an overall darkened visual perception to users if directly applied to VR content. Our key insight is that VR display power reduction must be cognizant of the gaze-contingent nature of high field-of-view VR displays. To that end, we present a gaze-contingent system that, without degrading luminance, minimizes the display power consumption while preserving high visual fidelity when users actively view immersive video sequences. This is enabled by constructing 1) a gaze-contingent color discrimination model through psychophysical studies, and 2) a display power model (with respect to pixel color) through real-device measurements. Critically, due to the careful design decisions made in constructing the two models, our algorithm is cast as a constrained optimization problem with a closed-form solution, which can be implemented as a real-time, image-space shader. We evaluate our system using a series of psychophysical studies and large-scale analyses on natural images. Experiment results show that our system reduces the display power by as much as 24% (14% on average) with little to no perceptual fidelity degradation.

An automated method for BRISQUE quantification of image quality in echocardiography

Abstract Background Echocardiography (echo) remains the most widely used imaging modality for the assessment, monitoring, and prognostication of the heart. Despite its prevalence, standardisation efforts for echo chamber quantification are ongoing, with challenges owing to subjectivity during acquisition and analysis. Furthermore, the confidence in derived functional indices is often dependent on the quality of the acquired images. However, few studies have investigated the accuracy of echo measurements compared to a reference modality such as cardiac magnetic resonance (CMR) imaging, when stratified by image quality. Purpose To develop an objective and automated method to quantify echo image quality, and subsequently to investigate the relationship between image quality and patient demographics, as well as the magnitude of bias in left ventricular (LV) functional indices compared with CMR. Methods Transthoracic apical 2D echo (2DE) and 3D echo (3DE) data from 128 participants (72 healthy controls and 56 patients with acquired heart disease) were used to train a BRISQUE (Blind/Referenceless Image Spatial Quality Evaluator) algorithm [1]. Briefly, feature extraction was performed by fitting pixel luminances to a generalised Gaussian distribution (GGD), followed by support vector regression to correlate features (i.e., shape, variance, and mean parameters of the GGD) to quality scores (Fig. 1). Independent BRISQUE models were trained on 580 2DE images (consisting of 2-, 3-, and 4-chamber views) and 128 targeted LV 3DE acquisitions at end-diastole, each assigned a subjective perceived quality score between 1 (poor) and 9 (excellent) by a single observer. LV indices including end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), and global longitudinal strain (GLS), were assessed according to standard guidelines. Resultant BRISQUE scores were plotted against patient demographics (age, height, weight) and the measurement bias by comparison to CMR (acquired within 1 hour of echo). Results Several linear relationships (where P-value of slope <0.05) were observed between demographics, cardiac indices, and BRISQUE scores. Increasing patient weight (and height in 3DE) were found to be associated with poorer image quality. There was no apparent relationship between image quality and age. Of interest, EF exhibited a relationship with image quality in both 2DE and 3DE (Fig. 2), whereby higher quality images tended to overestimate EF, while lower quality images underestimated EF. For 3DE, image quality dependency was also observed for ESV and GLS biases. Conclusions BRISQUE can objectively quantify image quality to produce scores which correlate to those of an expert observer, with potential utility for the standardised quantification of echo image quality. Using this method, it may be possible to predict patient characteristics which adversely impact echo quality, as well as the magnitude of measurement biases for certain functional indices. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Health Research Council (HRC) of New Zealand; National Heart Foundation (NHF) of New Zealand

16.1: Invited Paper: Measurement of Perceived Pixel Luminance of Large LED Displays

Large screen LED displays are becoming increasingly popular. The human eye has a resolution of 1/60 degree, so at very close viewing the LED chips may be more easily seen because LED screens have a larger pixel pitch than traditional display technologies, unlike OLEDs and LCDs. In large LED displays, the perceived luminance of the pixels is highly dependent on the viewing distance and FOV. The paper examines the perceived pixel luminance of a large screen LED display at different viewing distances and field of views. Additionally, stray light was examined and discussed. The results indicated that the perceived pixel luminance can be significantly different under different viewing distances and FOVs. For future LED display performance evaluation, it would be advantageous to have a measuring device with high resolution that mimics the human eye's angular resolution in perceived pixel luminance.

Detection of Concrete Damage by X-ray CT and Related Non-destructive Elastic Wave Monitoring in Core Test

As a detailed inspection of a concrete structure in service, core samples are usually drilled out and then mechanical properties are measured. In this study, damage estimation of freeze-thawed concrete from concrete-core samples is developed, applying X-ray CT with machine learning method. By the authors, the quantitative damage evaluation of concrete has been proposed by applying acoustic emission and damage mechanics in core concrete. In this study, detection of cracking damage distribution in concrete-core by decision tree method. Prior to the machine learning analysis, distribution of micro-cracks in a concrete-core sample is inspected by helical X-ray computer tomography (CT). Two feature values are set as explanatory variables: luminance value and pixel value after DoG (Difference of Gaussian) filter. The evaluation values converged from the sample size of 12,000 or more. This suggests that one cross section can be estimated with about 50% of the X-ray CT image data by using machine learning. The accuracy rate is 0.723 for the threshold processing and 0.793 for the decision tree method, which is higher for the decision tree method. These results suggest that the proposed method is useful for identifying cracks in concrete by X-ray CT image.

The impact of image degradation and temporal dynamics on sustained attention.

Many clinical populations that have sustained attention deficits also have visual deficits. Therefore, it is necessary to understand how the quality of visual input and different forms of image degradation can contribute to worse performance on sustained attention tasks, particularly those with dynamic and complex visual stimuli. This study investigated the impact of image degradation on an adapted version of the gradual-onset continuous performance task (gradCPT), where participants must discriminate between gradually fading city and mountain scenes. Thirty-six normal-vision participants completed the task, which featured two blocks of six resolution and contrast levels. Subjects either completed a version with gradually fading or static image presentations. The results show decreases in image resolution impair performance under both types of temporal dynamics, whereas performance is only impaired under gradual temporal dynamics for decreases in image contrast. Image similarity analyses showed that performance has a higher association with an observer's ability to gather an image's global spatial layout (i.e. gist) than local variations in pixel luminance, particularly under gradual image presentation. This work suggests that gradually fading attention paradigms are sensitive to deficits in primary visual function, potentially leading to these issues being misinterpreted as attentional failures.

COMPARATIVE ANALYSIS OF FRACTAL DIMENSIONS OF HUMAN CEREBELLUM: IMPACT OF IMAGE PREPROCESSING AND FRACTAL ANALYSIS METHODS

The aim: To compare the values of the fractal dimensions of human cerebellum obtained using different algorithms of image preprocessing and different methods of fractal analysis. Materials and methods: The study involved 120 people without structural changes in the brain (age 18-86 years, 55 men and 65 women). T1- and T2-weighted MR brain images were studied. Fractal analysis was performed using box counting and pixel dilatation methods. Fractal dimensions of cerebellar tissue as a whole, cerebellar cortex and its individual layers, cerebellar white matter were measured and compared to each other and to fractal dimension of cerebellar white matter determined in cadaveric cerebella. Results: It was no significant difference between fractal dimension values of cerebellar tissue as a whole measured on T1 and T2 weighted magnetic resonance images of cerebellum, and fractal dimension values measured on the same images using different methods of fractal analysis – pixel dilatation and box counting. T2 weighted images are preferable for fractal analysis of different components of cerebellar tissue. Segmentation according to pixel luminance is the preferable image preprocessing method for fractal analysis of cerebellar cortex as a whole, individual cortical layers and cerebellar tissue as a whole; skeletonizing of cerebellar magnetic resonance images is the preferable method of the image preprocessing for fractal analysis of cerebellar white matter. Conclusions: The algorithm of image preprocessing, magnetic resonance imaging sequence and method of fractal analysis should be chosen according to aim of quantitative study of cerebellar magnetic resonance images and features of the studied structure of cerebellum.

Spatiotemporal Characterization of VIIRS Night Light

The Visible Infrared Imaging Radiometer Suite (VIIRS) Day Night Band (DNB) on board the Suomi NPP satellite now provides almost a decade of daily observations of night light. The temporal frequency of sampling, without the degree of temporal averaging of annual composites, makes it necessary to consider the distinction between apparent temporal changes of night light related to the imaging process and actual changes in the underlying sources of the night light being imaged. The most common approach to night light change detection involves direct attribution of observed changes to the phenomenon of interest. Implicit in this approach is the assumption that other forms of actual and apparent change in the light source are negligible or non-existent. An alternative approach is to characterize the spatiotemporal variability prior to deductive attribution of causation so that the attribution can be made in the context of the full range of spatial and temporal variation. The primary objective of this study is to characterize night light variability over a range of spatial and temporal scales to provide a context for interpretation of night light changes observed on both subannual and interannual time scales. This analysis is based on a combination of temporal moments, spatial correlation and Empirical Orthogonal Function (EOF) analysis. A key result of this study is the pervasive heteroskedasticity of VIIRS monthly mean night light. Specifically, the monotonic decrease of variability with increasing mean brightness. Anthropogenic night light is remarkably stable on subannual time scales while background luminance varies considerably. The variance partition from the eigenvalues of the spatiotemporal covariance matrix are 88, 2 and 2% for spatial, seasonal and interannual variance (respectively) in the most diverse region on Earth (Eurasia). Heteroskedasticity is pervasive in the monthly composites; present in all areas for all months of the year, suggesting that much, if not most, of the month-to-month variability may be related to luminance of otherwise stable sources subjected to multiple aspects of the imaging process varying in time. Given the skewed distribution of all night light arising from radial peripheral dimming of bright sources subject to atmospheric scattering, even aggregate metrics using thresholds must be interpreted in light of the fact that much larger numbers of more variable low luminance pixels may statistically overwhelm smaller numbers of stable higher luminance pixels and cause apparent changes related to the imaging process to be interpreted as actual changes in the light sources.

Design of Driving Waveform for Shortening Response Time of Black Particles and White Particles in Three-Color Electrophoretic Displays.

The shortage of color in traditional electrophoretic displays (EPDs) can be compensated by three-color EPDs. However, the response time of black particles and white particles is increased. A new driving waveform based on the principle of three-color EPDs and electrophoresis theory was proposed to shorten the response time of black particles and white particles. The proposed driving waveform consisted of an erasing stage, an activation stage, a red driving stage, and a white or a black driving stage. The activation stage was mainly optimized in this paper. Firstly, the motion characteristics of the particles were analyzed using Stokes law and electrophoresis theory. Secondly, an optimal high frequency oscillation voltage was tested in order to improve the activity of the particles. Then, the influence of oscillation period and oscillation times on the activation stage were analyzed for optimizing the reference grayscale. According to the luminance of pixels, an oscillation period of 30 ms and an oscillation time of 30 were determined. The experimental results showed that the response time of black particles was shortened by 45%, and the response time of white particles was shortened by 40% compared with a traditional driving waveform.

Computer monitor pixellation and Landolt C visual acuity.

To investigate the effects of computer monitor pixel density on Landolt C visual acuity measurements and to provide appropriate pixel density recommendations for Landolt C vision chart design. Participants were 10healthy observers aged 18-31years (mean 21.7±3.6). Logarithmic progression charts were used, consisting of eight rows of five Landolt C optotypes ranging from -0.40logMAR to 0.30logMAR. Monitor pixel angular subtense varied from 0.10min arc to 1.97min arc, achieved by changing the chart test distance. Testing took place with two filtering conditions: unfiltered optotypes, (pixels rendered either black or white) and anti-aliased optotypes with pixel luminance averaged for a pixel square and rendered as grey levels. Each participant's acuity versus pixel size data sets were fitted by a nonlinear relationship with acuity equal to an asymptotic threshold visual acuity (VAas )for small pixel sizes below a critical pixel size (Pcrit ). For pixel sizes larger than Pcrit there was a linear relationship between acuity thresholds and pixel size. For anti-aliased Landolt Cs, mean Pcrit was 1.23min, and for unfiltered Landolt Cs average Pcrit was 0.65min. For anti-aliased LandoltCs, Pcrit was 2.01xVAas , and for unfiltered Landolt Cs Pcrit was 1.05xVAas . These results are quantitatively very similar to previous research on pixellation and Sloan optotype acuity. We have demonstrated that spatially filtering Landolt C optotypes acts as anti-aliasing, to make them more robust to the degradation effects of pixellation. Previous recommendations for maximum pixel size on Sloan letter vision charts can be applied safely to Landolt C charts.