Random Noise Patterns Research Articles

The Impact of Bias Row Noise to Photometric Accuracy: Case Study Based on a Scientific CMOS Detector

We tested a new model of CMOS detector manufactured by the Gpixel Inc, for potential space astronomical application. In laboratory, we obtain some bias images under the typical application environment. In these bias images, clear random row noise pattern is observed. The row noise also contains some characteristic spatial frequencies. We quantitatively estimated the impact of this feature to photometric measurements, by making simulated images. We compared different bias noise types under strict parameter control. The result shows the row noise will significantly deteriorate the photometric accuracy. It effectively increases the readout noise by a factor of 2–10. However, if it is properly removed, the image quality and photometric accuracy will be significantly improved.

Context-dependent selectivity to natural images in the retina

Retina ganglion cells extract specific features from natural scenes and send this information to the brain. In particular, they respond to local light increase (ON responses), and/or decrease (OFF). However, it is unclear if this ON-OFF selectivity, characterized with synthetic stimuli, is maintained under natural scene stimulation. Here we recorded ganglion cell responses to natural images slightly perturbed by random noise patterns to determine their selectivity during natural stimulation. The ON-OFF selectivity strongly depended on the specific image. A single ganglion cell can signal luminance increase for one image, and luminance decrease for another. Modeling and experiments showed that this resulted from the non-linear combination of different retinal pathways. Despite the versatility of the ON-OFF selectivity, a systematic analysis demonstrated that contrast was reliably encoded in these responses. Our perturbative approach uncovered the selectivity of retinal ganglion cells to more complex features than initially thought.

Mental Representations and Facial Impressions of Muslim Men in Japan From 2015 to 2017

There is prejudice against Muslims in many nations, including Japan. This prejudice would be related to biased mental representations of Muslim faces. Moreover, in 2015, the increased news coverage linking Muslims to terrorism in Japan would have enhanced such negative mental representations. In the present study, Japanese participants were asked to imagine Muslim men, and from two faces with a random noise pattern added, participants were instructed to choose the face they imagined to be more Muslim. Typical Muslim facial representations were visualized in 2015, 2016, and 2017 by averaging all selected noise patterns using reverse correlation. The visualized representations were evaluated using the dimensions of warmth, competence, and basic emotions. The results showed that the warmth scores for the visualized facial representation were lower in 2015 than in 2017, whereas competence scores did not differ between the representations in 2015, 2016, and 2017. “Angry” and “disgusted” scores for the facial representation in 2015 were higher than those in 2017, whereas “happy” scores in 2015 were lower than those in 2017. The decreased “angry” score and increased “happy” score predicted an increase in the impression of warmth from 2015 to 2017.

Beyond attractiveness: A multimethod approach to study enhancement in self-recognition on the Big Two personality dimensions.

Self-enhancement refers to the phenomenon that individuals tend to have unrealistically positive self-views. Traditional measures of self-enhancement typically imply self-evaluations and reference values, such as evaluations by others or evaluations of the average other. Comparing individuals' self-evaluations with such reference values, however, bears risks. It is not evident that the reference values are more accurate than the self-evaluations and it is not possible to distinguish self-enhancers from individuals who are indeed superior to others. Here, we present two novel methods to measure self-enhancement that circumvent these problems by using participants' own faces as reference values. In Study 1 we systematically manipulate facial characteristics that have previously been found to impact perceptions of attractiveness, likability, and the Big Two personality dimensions in participants' faces and ask them to recognize themselves. In Study 2 we use a novel approach to apply random noise patterns to participants' faces and ask them to indicate in which version they recognize themselves more. Aggregating these random noise patterns reveals the direction of self-recognition in a more bottom-up, data-driven way. Across both studies we find evidence for self-enhancement regarding attractiveness, likability, and the Big Two personality dimensions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Face perception inherits low-level binocular adaptation.

In previous work (May & Zhaoping, 2016; May, Zhaoping, & Hibbard, 2012), we have provided evidence that the visual system efficiently encodes binocular information using separately adaptable binocular summation and differencing channels. In that work, binocular test stimuli delivered different grating patterns to the two binocular channels; selective adaptation of one of the binocular channels made participants more likely to see the other channel's grating pattern. In the current study, we extend this paradigm to face perception. Our test stimuli delivered different face images to the two binocular channels, and we found that selective adaptation of one binocular channel biased the observer to perceive the other channel's face image. We show that the perceived identity, gender, emotional expression, or direction of 3-D rotation of a facial test image can be influenced by pre-exposure to binocular random-noise patterns that contain no meaningful spatial structure. Our results provide compelling evidence that face-processing mechanisms can inherit adaptation from low-level sites. Our adaptation paradigm targets the low-level mechanisms in such a way that any response bias or inadvertent adaptation of high-level mechanisms selective for face categories would reduce, rather than produce, the measured effects of adaptation.

ROBUST WATERMARKING TECHNIQUE USING DIFFERENT WAVELET DECOMPOSITION LEVELS FOR SIGNATURE IMAGE PROTECTION

This paper proposed a non-blind watermarking technique based on different wavelet decomposition levels for biometric image protection. In this technique, a biometric image is used as a watermark instead of a standard image, logo or random noise pattern type watermark. For watermark embedding, the original host image and the watermark biometric image are transformed into various levels of wavelet coefficients. The watermark biometric image is embedded into the host image by modifying the values of the wavelet coefficients of the host image using the values of wavelet coefficients of the watermark biometric image. Experimental results demonstrated that the proposed technique was able to withstand various watermarking attacks. The novelty of the proposed technique is that it is used to transform coefficients of the watermark biometric image instead of the Pseudo Noise sequences or any other feature extraction technique.

Depth perception in autostereograms: 1/f noise is best.

An autostereogram is a single image that encodes depth information that pops out when looking at it. The trick is achieved by setting a basic 2D pattern and continuously replicating the local pattern at each point in the image with a shift defined by the desired disparity. In this work, we explore the dependency between the ease of perceiving depth in autostereograms and the choice of the basic pattern used for generating them. We report the results of three sets of psychophysical experiments using autostereograms generated from 2D random noise patterns having power spectra of the form 1/f(β) The experiments were designed to test the ability of human subjects to identify smooth low-resolution surfaces, as well as detail, in the form of higher-resolution objects in the depth profile, and to determine limits in identifying small objects as a function of their size. In accordance with the theory, we discover a significant advantage of the 1/f noise pattern (pink noise) for fast depth lock-in and fine detail detection, showing that such patterns are optimal choices for autostereogram design.

Semi-Local Structure Patterns for Robust Face Detection

In many image processing and computer vision problems, including face detection, local structure patterns such as local binary patterns (LBP) and modified census transform (MCT) have been adopted in widespread applications due to their robustness against illumination changes. However, being reliant on the local differences between neighboring pixels, they are inevitably sensitive to noise. To overcome the problem of noise-vulnerability of the conventional local structure patterns, we propose semi-local structure patterns (SLSP), a novel feature extraction method based on local region-based differences. The SLSP is robust to illumination variations, distortion, and sparse noise because it encodes the relative sizes of the central region with locally neighboring regions into a binary code. The principle of SLSP leads noise-robust expansions of LBP and MCT feature extraction frameworks. In a statistical analysis, we find that the proposed methods transform a substantial amount of random noise patterns in face images into more meaningful uniform patterns. The empirical results on the ${\rm MIT} + {\rm CMU}$ dataset and FDDB (face detection dataset and benchmark) show that the proposed semi-local patterns applied to LBP and MCT feature extraction frameworks outperform the conventional LBP and MCT features in AdaBoost-based face detectors, with much higher detection rates.

A lower bound on the number of mechanisms for discriminating fourth and higher order spatial correlations

Research on single striate cortical neurons has often concentrated on their responses to stimuli defined by two-point correlations. Texture discrimination studies using a relatively small palette of isotrigon textures have indicated that we are sensitive to third and higher-order spatial correlations.To further evaluate the underlying mechanisms of texture discrimination subjects discriminated random binary noise patterns from ten new isotrigon texture types.Factor analysis revealed that as few as three mechanisms may govern the detection of fourth and higher order image structure. This supports the findings of previous studies using different isotrigon textures.The computation of higher-order correlations by the brain is neurophysiologically plausible. The mechanisms identified in this study may represent some short range nonlinear combination of recursive and/or rectifying processes.

Invisible visual stimuli elicit increases in alpha-band power.

The cerebral cortex responds to stimuli of a wide range of intensities. Previous studies have demonstrated that undetectably weak somatosensory stimuli cause a functional deactivation or inhibition in somatosensory cortex. In the present study, we tested whether invisible visual stimuli lead to similar responses, indicated by an increase in EEG alpha-band power-an index of cortical excitability. We presented subliminal and supraliminal visual stimuli after estimating each participant's detection threshold. Stimuli consisted of peripherally presented small circular patches that differed in their contrast to a background consisting of a random white noise pattern. We demonstrate that subliminal and supraliminal stimuli each elicit specific neuronal response patterns. Supraliminal stimuli evoked an early, strongly phase-locked lower-frequency response representing the evoked potential and induced a decrease in alpha-band power from 400 ms on. By contrast, subliminal visual stimuli induced an increase of non-phase-locked power around 300 ms that was maximal within the alpha-band. This response might be due to an inhibitory mechanism, which reduces spurious visual activation that is unlikely to result from external stimuli.

Monitoring neural stem cell differentiation using PEDOT–PSS based MEA

BackgroundTransplantation is one potential clinical application of neural stem cells (NSCs). However, it is very difficult to monitor/control NSCs after transplantation and so provide effective treatment. Electrical measurement using a poly(3,4-ethylenedioxythiophene)–poly(styrenesulfonate) (PEDOT–PSS) modified microelectrode array (MEA) is a biocompatible, non-invasive, non-destructive approach to understanding cell conditions. This property makes continuous monitoring available for the evaluation/assessment of the development of cells such as NSCs. MethodsA PEDOT–PSS modified MEA was used to monitor electrical signals during NSC development in a culture derived from rat embryo striatum in order to understand the NSC differentiation conditions. ResultsElectrical data indicated that NSCs with nerve growth factor (NGF) generate a cultured cortical neuron-like burst pattern while a random noise pattern was measured with epidermal growth factor (EGF) at 4days in vitro (DIV) and a burst pattern was observed in both cases at 11 DIV indicating the successful monitoring of differentiation differences and developmental changes. ConclusionsThe electrical analysis of cell activity using a PEDOT–PSS modified MEA could indicate neural network formation by differentiated neurons. Changes in NSC differentiation could be monitored. General significanceThe method is based on non-invasive continuous measurement and so could prove a useful tool for the primary/preliminary evaluation of a pharmaceutical analysis. This article is part of a Special Issue entitled Organic Bioelectronics—Novel Applications in Biomedicine.

Visual short‐term memory for unfamiliar visual stimuli

Purpose: Visual short‐term memory (VSTM) for briefly presented visual stimuli has been estimated at 4–6 items for real‐world objects (Luck and Vogel, 1997). To measure the fundamental capacity of VSTM the use of real‐world objects is undesirable, since estimates are confounded by verbal descriptors and/or long‐term memory support (Olsson and Poom, 2005). The purpose of this study is to measure the accuracy and capacity of VSTM for unfamiliar, non‐categorical visual stimuli.Method: Stimuli were random grayscale noise patterns subtending 2°× 2, displayed at a distance of 57 cm. A series of reference stimuli were presented sequentially at the centre of a computer display for 500 ms each. Following this, a blank interval of 500 ms, and then a test stimulus were displayed. Signal present test stimuli originated from a random index in the study series. The probability of a signal present trial was 50%. Observers were instructed to indicate, via a numeric keypad, if the test stimulus was present in the study series (yes/no). Series length was increased from 1 to 5 across blocks of trials. The number of blocks completed for each series length, S, was 2S, where each block comprised 100 trials (i.e. 3000 trials per observer were completed). Four normal/corrected‐to‐normal observers participated in the study. The number of objects encoded in VSTM was calculated using Cowan's formula (Cowan, 2001).Results: Across series lengths 1–5, average performance rate (pooled across observers) decreased exponentially from 95% for series length 1, to 60% for series length 5. The number of stimuli encoded in VSTM, determined using Cowan's formula, was found to be 1.52, achieved for series length 3. Beyond series length 3, the number of items encoded was found to decrease, at 0.92, 1.30, 1.52, 1.35 and 1.40 for series lengths 1–5, respectively. For series lengths > 1, large recency effects were found by analysis of the reference indices of correctly identified signal present test stimuli.Conclusions: We find that the capacity of VSTM for serially presented non‐categorical visual stimuli is limited to 1.5 items, in line with VSTM capacity estimates of Olsson and Poom (2005), rather than the more commonly cited 4–6 items (Cowan, 2001; Luck and Vogel, 1997), and is seen to decrease exponentially with increases in series length or decreases in recency. A suite of related experiments are underway to construct a memory performance model under varying stimulus presentation scenarios, including parallel display and variable location.

Detail-preserving image information restoration guided by SVM based noise mapping

In this paper, we propose a new method to solve the problem of fixed-valued impulsive noise reduction in images. Nonlinear filter like the median filter (MF) is useful for reducing random noise and periodical patterns, but direct median filtering have undesirable side effects such as smoothening of noise free regions, which results in loss of image detail and distortion of the signal. Impulse noise is suppressed by selectively filtering the contaminated signal regions only, thus minimizing distortion of clean passages and loss of high frequencies. In the first phase, support vector machines (SVM) are used to segment the set of pixels N that are likely to be contaminated by the mixed impulses. In the second phase, the image is restored by employing a combination of the best neighborhood match filter (BNM) and the modified multi-shell median filter (MMMF) to these segmented regions. This method combines the effectiveness of the best neighborhood matching (BNM) filter in suppression of the noise components while adapting itself to the local image structures, and the edge and finer image detail preserving characteristics of the MMMF. To support our proposed method, numerical results are also provided, which indicate that the filter is extremely useful for preserving edges or monotonic changes in trend, while eliminating short duration impulses of high density.

How Do Lesion Size and Random Noise Affect Detection Performance in Digital Mammography?

We investigated the effect of random noise and lesion size on detection performance in mammography. Digital mammograms were obtained of an anthropomorphic breast phantom with and without simulated mass lesions. Digital versions of the mass lesions, ranging in size from 0.8 to 12 mm, were added back to the breast phantom image. Four alternate forced choice experiments were performed to determine the lesion contrast required to achieve a 92% correct lesion detection rate, denoted I92. Experiments were performed using identical phantom images and different versions of phantom images obtained using the same techniques but with different random noise patterns. For lesions larger than 1 mm, the slope of the contrast detail curves was always positive. This behavior contrasts with conventional contrast-detail curves in uniform backgrounds in which the slope is approximately -0.5. There was no difference between twinned experiments and those obtained using different patterns of random noise for lesions greater than 1 mm. When the lesion size was reduced below 1 mm, the detection threshold increased indicating a deterioration of lesion detectability, and detection performance was significantly lower when random noise patterns were used. Our results suggest that lesion detection is dominated by anatomical structure for lesions with a size >1 mm, but by random noise for submillimeter sized lesions.

Resolution for spatial segregation and spatial localization by motion signals

We investigated two types of spatial resolution for perceiving motion-defined contours: grating acuity, the capacity to discriminate alternating stripes of opposed motion from transparent bi-directional motion; and alignment acuity, the capacity to localize the position of motion-defined edges with respect to stationary markers. For both tasks the stimuli were random noise patterns, low-pass filtered in the spatial dimension parallel to the motion. Both grating and alignment resolution varied systematically with spatial frequency cutoff and speed. Best performance for grating resolution was about 10 c/deg (for unfiltered patterns moving at 1–4 deg/s), corresponding to a stripe resolution of about 3′. Grating resolution corresponds well to estimates of smallest receptive field size of motion units under these conditions, suggesting that opposing signals from units with small receptive fields (probably located in V1) are contrasted efficiently to define edges. Alignment resolution was about 2′ at best, under similar conditions. Whereas alignment judgment based on luminance-defined edges is typically 3–10 times better than resolution, alignment based on motion-defined edges is only 1.1–1.5 times better, suggesting motion contours are less effectively encoded than luminance contours.

The effects of static multiple sources of noise on the visual search component of human inspection

Visual inspection is a commonly used inspection method, but effects of noise on visual inspection have not been studied extensively. The objective of this study was to investigate the effects of noise on visual search performance. The effects of continuous, intermittent, and random noise conditions emitted from single and multiple sources on the accuracy of an inspector to perform easy and difficult inspection tasks was examined. When compared to the continuous noise treatment, random and intermittent noise patterns were shown to have negative effects on the easy search task accuracy. Additionally, the results indicate that single source noise enhances search performance of difficult tasks. A larger study would likely detect noxious effects of multiple noise sources on difficult search task performance. Relevance to industry A thorough understanding of inspection is important for continued quality, reliability and safety in manufacturing, maintenance, security and other industries. The results of this study can be applied to inspection tasks conducted in workplace conditions that are similar to those employed in the current study.

Contrast conservation in human vision

Visual experience, which is defined by brief saccadic sampling of complex scenes at high contrast, has typically been studied with static gratings at threshold contrast. To investigate how suprathreshold visual processing is related to threshold vision, we tested the temporal integration of contrast in the presence of large, sudden changes in the stimuli such occur during saccades under natural conditions. We observed completely different effects under threshold and suprathreshold viewing conditions. The threshold contrast of successively presented gratings that were either perpendicularly oriented or of inverted phase showed probability summation, implying no detectable interaction between independent visual detectors. However, at suprathreshold levels we found complete algebraic summation of contrast for stimuli longer than 53 ms. The same results were obtained during sudden changes between random noise patterns and between natural scenes. These results cannot be explained by traditional contrast gain-control mechanisms or the effect of contrast constancy. Rather, at suprathreshold levels, the visual system seems to conserve the contrast information from recently viewed images, perhaps for the efficient assessment of the contrast of the visual scene while the eye saccades from place to place.

Perceptual anisotropies in visual processing and their relation to natural image statistics

The amplitude spectra of natural scenes are typically biased in terms of the amount of content at the cardinal orientations relative to the oblique orientations. This anisotropic distribution has been related to the 'oblique effect' (the greater visual sensitivity for simple line/grating stimuli at cardinal compared to oblique orientations). However, we have recently shown that with complex visual stimuli possessing broadband spatial content (i.e. random phase noise patterns), sensitivity for detecting oriented manipulations of amplitude is best for oblique orientations, and worst for horizontal orientations (the 'horizontal effect'). Here we investigated this effect with respect to the phase spectra of natural scenes. Oriented manipulations of both amplitude and phase were made on a set of natural scene images that were dominated by naturally occurring structure at one of four orientations in order to determine whether the presence of predominant scene content, carried by the Fourier phase spectra, altered the ability to detect an oriented increment of amplitude. The horizontal effect was observed regardless of any scene's content bias. In addition, a content-dependent effect was observed which could be related to the presence of spatial structure conveyed by the phase spectra of this set of natural scenes. Results are evaluated in the context of a divisive normalization model.

Perceptual anisotropies in visual processing and their relation to natural image statistics

The amplitude spectra of natural scenes are typically biased in terms of the amount of content at the cardinal orientations relative to the oblique orientations. This anisotropic distribution has been related to the ‘oblique effect’ (the greater visual sensitivity for simple line/grating stimuli at cardinal compared to oblique orientations). However, we have recently shown that with complex visual stimuli possessing broadband spatial content (i.e. random phase noise patterns), sensitivity for detecting oriented manipulations of amplitude is best for oblique orientations, and worst for horizontal orientations (the ‘horizontal effect’). Here we investigated this effect with respect to the phase spectra of natural scenes. Oriented manipulations of both amplitude and phase were made on a set of natural scene images that were dominated by naturally occurring structure at one of four orientations in order to determine whether the presence of predominant scene content, carried by the Fourier phase spectra, altered the ability to detect an oriented increment of amplitude. The horizontal effect was observed regardless of any scene's content bias. In addition, a content-dependent effect was observed which could be related to the presence of spatial structure conveyed by the phase spectra of this set of natural scenes. Results are evaluated in the context of a divisive normalization model.

Correlations between patterns of 19th and 20th century surface temperature change and HadCM2 Climate Model ensembles

We examine the similarity between patterns of changes in decadally‐averaged surface air temperature simulated by ensemble experiments with the HadCM2 coupled climate model and observed patterns over the period 1860–1999, using a spatial pattern correlation method. The analysis is conducted for two anthropogenic (greenhouse gases with/without sulphate aerosols) and two natural (solar and volcanic) modelled forcing histories. For each scenario an ensemble of at least four model runs is used. We compare transient model signal and observed patterns at corresponding times, and establish significance using a 1000 year model control run to construct sampling distributions for random noise patterns. We find evidence of an anthropogenic signal in observed surface temperature patterns emerging over recent decades, particularly in northern winter and spring seasons. Signals from greenhouse gas forcing alone or in combination with sulphate aerosols are both plausible in our analysis, but the highest significance is achieved using seasonally‐defined greenhouse gas plus aerosol signals. There is little evidence of any detectable solar signal, but we do find two periods (late 19th century; 1960s–90s) during which a weak volcanic signal is detectable. Using ensemble simulations makes the conclusions quite robust, but the somewhat different interpretations from this analysis compared to optimal fingerprint analysis of the same simulations reveals some sensitivity to the choice of methodology.