RMS Contrast Research Articles

A Low-Cost Remotely Configurable Electronic Trap for Insect Pest Dataset Generation

The precise monitoring of insect pest populations is the foundation of Integrated Pest Management (IPM) for pests of plants, humans, and animals. Digital technologies can be employed to address one of the main challenges, such as reducing the IPM workload and enhancing decision-making accuracy. In this study, digital technologies are used to deploy an automated trap for capturing images of insects and generating centralized repositories on a server. Subsequently, advanced computational models can be applied to analyze the collected data. The study provides a detailed description of the prototype, designed with a particular focus on its remote reconfigurability to optimize repository quality; and the server, accessible via an API interface to enhance system interoperability and scalability. Quality metrics are presented through an experimental study conducted on the constructed demonstrator, emphasizing trap reliability, stability, performance, and energy consumption, along with an objective analysis of image quality using metrics such as RMS contrast, Image Entropy, Image sharpness metric, Natural Image Quality Evaluator (NIQE), and Modulation Transfer Function (MFT). This study contributes to the optimization of the current knowledge regarding automated insect pest monitoring techniques and offers advanced solutions for the current systems.

Blind Deblurring Method for CASEarth Multispectral Images Based on Inter-Band Gradient Similarity Prior.

Multispectral remote sensing images contain abundant information about the distribution and reflectance of ground objects, playing a crucial role in target detection, environmental monitoring, and resource exploration. However, due to the complexity of the imaging process in multispectral remote sensing, image blur is inevitable, and the blur kernel is typically unknown. In recent years, many researchers have focused on blind image deblurring, but most of these methods are based on single-band images. When applied to CASEarth satellite multispectral images, the spectral correlation is unutilized. To address this limitation, this paper proposes a novel approach that leverages the characteristics of multispectral data more effectively. We introduce an inter-band gradient similarity prior and incorporate it into the patch-wise minimal pixel (PMP)-based deblurring model. This approach aims to utilize the spectral correlation across bands to improve deblurring performance. A solution algorithm is established by combining the half-quadratic splitting method with alternating minimization. Subjectively, the final experiments on CASEarth multispectral images demonstrate that the proposed method offers good visual effects while enhancing edge sharpness. Objectively, our method leads to an average improvement in point sharpness by a factor of 1.6, an increase in edge strength level by a factor of 1.17, and an enhancement in RMS contrast by a factor of 1.11.

Higher-contrast images are better remembered during naturalistic encoding

It is unclear whether memory for images of poorer visibility (as low contrast or small size) will be lower due to weak signals elicited in early visual processing stages, or perhaps better since their processing may entail top-down processes (as effort and attention) associated with deeper encoding. We have recently shown that during naturalistic encoding (free viewing without task-related modulations), for image sizes between 3°–24°, bigger images stimulating more visual system processing resources at early processing stages are better remembered. Similar to size, higher contrast leads to higher activity in early visual processing. Therefore, here we hypothesized that during naturalistic encoding, at critical visibility ranges, higher contrast images will lead to higher signal-to-noise ratio and better signal quality flowing downstream and will thus be better remembered. Indeed, we found that during naturalistic encoding higher contrast images were remembered better than lower contrast ones (~ 15% higher accuracy, ~ 1.58 times better) for images at 7.5–60 RMS contrast range. Although image contrast and size modulate early visual processing very differently, our results further substantiate that at poor visibility ranges, during naturalistic non-instructed visual behavior, physical image dimensions (contributing to image visibility) impact image memory.

A quantitative method for localizing RMS contrast in egocentric images

A quantitative method for localizing RMS contrast in egocentric images

DMD-based optical pattern recognition using holograms generated with the Hartley transform

High-speed optical reconstruction of holographic and diffractive optical elements is widely used in encryption and recognition, 3D-displays, beam shaping, nanofabrication, visualization, etc. This paper proposes the use of amplitude holograms generated by the Hartley transform (HT) as filters in an incoherent correlator. The real computations using the HT are faster and less computationally intensive than the standard complex transforms. Generated holograms using HT and Fourier transform (FT) were compared. It is demonstrated that the diffraction efficiency of HT-based holograms is not inferior to the FT case. The reconstruction quality is better in metrics (NSTD, MSE, SNR, RMS contrast, SSIM) by 2–10%. An optical incoherent correlator based on two digital micromirror devices (DMDs) was constructed. DMDs have very high frame rates (up to 30 kHz) that provides its great potential for application in fast recognition problems. The object images were displayed on the first DMD. The holograms generated with the HT were binarized and displayed on the second DMD. The objects were successfully recognized. Thus, HT-based amplitude holograms can be successfully used instead of FT-based amplitude holograms.

The Effect of Monochromatic Aberrations of the Cornea on Contrast Sensitivity under Photopic and Mesopic Conditions

Purpose: Vision is one of the most important senses. The first stage of vision is the creation of the observed object’s image on the retina. The quality of the retinal image is affected by several factors, such as diffraction, sampling on the retina, chromatic aberration, scattering and higher order aberrations. The measurement of the quality is achieved both with subjective (visual acuity, contrast sensitivity) and objective methods (PSF, MTF, Strehl ratio, RMS). The purpose of this project is the measurement of higher order aberrations of the anterior corneal surface (with a Placido corneal topographer) and of the contrast sensitivity (with a Pelli Robson optotype). Then, we will try to find if there is a correlation between them.
 Methods and Materials: 20 persons participated in this survey, divided in two groups of 10 persons each. The first group (group 1) included subjects up to 39 years old and the second group (group 2) from 40 years and up. The participants didn’t have any pathological problems, except lower order refractive errors. Both eyes of each individual were included in the procedure. First, the higher order aberrations of the anterior corneal surface were measured, with the implementation of a Placido corneal topographer. This was followed by a measurement of the contrast sensitivity. The whole procedure took place under two lighting conditions, both photopic and mesopic. The examination presentation of the higher order aberrations is performed with the use of Zernike polynomials.
 Results: The results of the measuring procedure showed that for the first group, under photopic conditions (luminance 32.70 cd/m2) the mean value (± standard deviation) for the higher order aberrations RMS and decimal logarithm contrast sensitivity was 0.073 ± 0.018μm and 1.54 ± 0,16 (contrast 2.88 ± 1.24%) respectively. For the second group the corresponding values were 0.080 ± 0.036μm and 1.59 ± 0.16 (contrast 2.57 ± 1.24%). Accordingly, under mesopic conditions (luminance 1.14 cd/m2) the values for the first group were 0.252 ± 0.064 μm and 1.27 ± 0.15 (contrast 5.37 ± 2.06%), while for the second were 0.253 ± 0.069μm and 1.32 ± 0.12 (contrast 4.79 ± 1.35%). Spherical aberration and coma (horizontal and vertical) were also measured for both groups under photopic and mesopic conditions. The results showed that for the first group, under photopic conditions, RMS for coma and spherical aberration is 0.033 ± 0.014 μm and 0.022 ± 0.011 μm respectively, while for the second group 0.041 ± 0.027 μm and 0.024 ± 0.008 μm. Under mesopic conditions, the relevant results are 0.139 ± 0.065 μm and 0.124 ± 0.035μm for the first group and 0.149 ± 0.066 μm and 0.107 ± 0.038 μm for the second group.
 Finally, we should mention here that the equivalent defocus error corresponding to the higher order aberration RMS was estimated. The results for all the participants (without age separation), are 0.23 ± 0.09D (photopic conditions) and 0.28 ± 0.07D (mesopic conditions).
 Conclusions: From the statistical analysis of the results we conclude that there exists a symmetry between left and right eyes regarding higher order aberrations. Furthermore, it seems that age is not a significant factor for differences on the magnitude of higher order aberrations both under photopic and mesopic conditions as well. Similar conclusions are also reached for the contrast sensitivity measurements. In addition, we have observed that a correlation exists between the higher order aberrations of the anterior corneal surface and the contrast sensitivity, for both photopic and mesopic conditions. Correlation also exists between coma and contrast only under photopic conditions. But there is no significant correlation between spherical aberration and contrast. The age difference of these two groups has not an effect on the results. Finally, the equivalent defocus is too small, both for photopic and mesopic conditions and between each other, in order to be clinically significant.

Developing a Screening Tool for Areas of Abnormal Central Vision Using Visual Stimuli With Natural Scene Statistics.

PurposePrevious studies show that some visual field (VF) defects are detectable from visual search behavior; for example, when watching video. Here, we developed and tested a VF testing approach that measures the number of fixations to find targets on a background with spatial frequency content similar to natural scenes.MethodsTwenty-one older controls and 20 people with glaucoma participated. Participants searched for a Gabor (6 c/°) that appeared in one of 25 possible locations within a 15° (visual angle) 1/f noise background (RMS contrast: 0.20). Procedure performance was assessed by calculating sensitivity and specificity for different combinations of control performance limits (p = 95%, 98%, 99%), number of target locations with fixations outside control performance limits (k = 0 to 25) and number of repeated target presentations (n = 1 to 20).ResultsControls made a median of two to three fixations (twenty-fifth to seventy-fifth percentile: two to four) to locate the target depending on location. A VF was flagged “abnormal” when the number of fixations was greater than the p = 99% for k = 3 or more locations with n = 2 repeated presentations, giving 85% sensitivity and 95.2% specificity. The median test time for controls was 85.71 (twenty-fifth to seventy-fifth percentile: 66.49–113.53) seconds.ConclusionOur prototype test demonstrated effective and efficient screening of abnormal areas in central vision.Translational RelevanceVisual search behavior can be used to detect central vision loss and may produce results that relate well to performance in natural visual environments.

The Role of Specular Reflections and Illumination in the Perception of Thickness in Solid Transparent Objects.

Specular reflections and refractive distortions are complex image properties of solid transparent objects, but despite this complexity, we readily perceive the 3D shapes of these objects (e.g., glass and clear plastic). We have found in past work that relevant sources of scene complexity have differential effects on 3D shape perception, with specular reflections increasing perceived thickness, and refractive distortions decreasing perceived thickness. In an object with both elements, such as glass, the two optical properties may complement each other to support reliable perception of 3D shape. We investigated the relative dominance of specular reflection and refractive distortions in the perception of shape. Surprisingly, the ratio of specular reflection to refractive component was almost equal to that of ordinary glass and ice, which promote correct percepts of 3D shape. The results were also explained by the variance in local RMS contrast in stimulus images but may depend on overall luminance and contrast of the surrounding light field.

Contributed Session III: Assessing the neural coding of image blur using multivariate pattern analysis

Blur is a fundamental perceptual attribute of images, but the way in which the visual system encodes this attribute remains poorly understood. Previously, we examined the neural correlates of blur by measuring BOLD responses to in-focus images and their blurred or sharpened counterparts, formed by varying the slope of the amplitude spectra but maintaining constant RMS contrast (Tregillus et al. 2014). In visual cortex (V1-V4), highest activation occurred for in-focus images compared to blurred or sharpened images - a finding which counters expectations from norm-based or predictive coding but is consistent with other studies examining the effects of manipulating the 1/f amplitude spectrum (Olman et al. 2004; Isherwood et al. 2017). To further examine the representation of blur, here we reanalysed this dataset using multivariate pattern analysis and also expanded the analysis to include additional visual areas (VO1, VO2, V3AB, LO, TO). A linear classifier trained to distinguish blurred vs. sharpened images provided significant decoding irrespective of visual area, suggesting that information about blur may be preserved across much of the visual hierarchy. The decoding may reflect larger scale differences in the representation of spatial frequency information within regions (e.g. as a function of eccentricity) or a finer scale columnar organization.

Studies on visual health features of luminous environment in college classrooms

The light environments have an impact on the physiological and psychological environment by means of light and color to a certain degree, thereby affecting the visual health features. This study proposed to utilize a new index derived from clinical medicine, i.e., the root mean square contrast of ambient luminance to evaluate light environments. We explored the correlation among the RMS contrast and visual health features under non-glare conditions, so as to obtain the optimal luminance contrast range for visual health. We use visual task evaluation and physiological evaluation to represent visual health features. Eye-tracking glasses were utilized to record the physiological data of eyes, and the psychological software of E-Prime 3 was employed to record the efficiency data of visual tasks. Besides, the high dynamic range images were used to record light environment. The feasibility of the light environment evaluation by the RMS brightness contrast of the environment in the field of vision is verified experimentally. Through multiple regression analysis, an obvious relationship between the new index and the visual health features was obtained, and the best range of the new index was determined. The RMS contrast was typical within the range of [450,750] cd/m2, which ensures the visual health for good ocular performance and high work efficiency; in the case that this value exceeds 1000 cd/m2, visual health features will be adversely impacted. In this research, a comprehensive light comfort zone was proposed, which could present a valuable reference for the design of the indoor light environments.

Contrast normalisation masks natural expression-related differences and artificially enhances the perceived salience of fear expressions

Fearful facial expressions tend to be more salient than other expressions. This threat bias is to some extent driven by simple low-level image properties, rather than the high-level emotion interpretation of stimuli. It might be expected therefore that different expressions will, on average, have different physical contrasts. However, studies tend to normalise stimuli for RMS contrast, potentially removing a naturally-occurring difference in salience. We assessed whether images of faces differ in both physical and apparent contrast across expressions. We measured physical RMS contrast and the Fourier amplitude spectra of 5 emotional expressions prior to contrast normalisation. We also measured expression-related differences in perceived contrast. Fear expressions have a steeper Fourier amplitude slope compared to neutral and angry expressions, and consistently significantly lower contrast compared to other faces. This effect is more pronounced at higher spatial frequencies. With the exception of stimuli containing only low spatial frequencies, fear expressions appeared higher in contrast than a physically matched reference. These findings suggest that contrast normalisation artificially boosts the perceived salience of fear expressions; an effect that may account for perceptual biases observed for spatially filtered fear expressions.

The effect of facial expression on contrast sensitivity: A behavioural investigation and extension of Hedger, Adams & Garner (2015).

It has been argued that rapid visual processing for fearful face expressions is driven by the fact that effective contrast is higher in these faces compared to other expressions, when the contrast sensitivity function is taken into account. This proposal has been upheld by data from image analyses, but is yet to be tested at the behavioural level. The present study conducts a traditional contrast sensitivity task for face images of various facial expressions. Findings show that visual contrast thresholds do not differ for different facial expressions We re-conduct analysis of faces’ effective contrast, using the procedure developed by Hedger, Adams and Garner, and show that higher effective contrast in fearful face expressions relies on face images first being normalised for RMS contrast. When not normalised for RMS contrast, effective contrast in fear expressions is no different, or sometimes even lower, compared to other expressions. However, the effect of facial expression on detection in a backward masking study did not depend on the type of contrast normalisation used. These findings are discussed in relation to the implications of contrast normalisation on the salience of face expressions in behavioural and neurophysiological experiments, and also the extent that natural physical differences between facial stimuli are masked during stimulus standardisation and normalisation.

Generation of Solar UV and EUV Images from SDO/HMI Magnetograms by Deep Learning

Abstract In this Letter, we apply deep-learning methods to the image-to-image translation from solar magnetograms to solar ultraviolet (UV) and extreme UV (EUV) images. For this, We consider two convolutional neural network models with different loss functions, one (Model A) is with L1 loss (L 1), and the other (Model B) is with L 1 and cGAN loss (L cGAN). We train the models using pairs of Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) nine-passband (94, 131, 171, 193, 211, 304, 335, 1600, and 1700 Å) UV/EUV images and their corresponding SDO/Helioseismic and Magnetic Imager (HMI) line-of-sight (LOS) magnetograms from 2011 to 2016. We evaluate the models by comparing pairs of SDO/AIA images and the corresponding ones generated in 2017. Our main results from this study are as follows. First, the models successfully generate SDO/AIA-like solar UV and EUV images from SDO/HMI LOS magnetograms. Second, in view of three metrics (pixel-to-pixel correlation coefficient, relative error, and the percentage of pixels having errors less than 10%), the results from Model A are mostly comparable or slightly better than those from Model B. Third, in view of the rms contrast measure, the generated images by Model A are much more blurred than those by Model B because of L cGAN specialized for generating realistic images.

A GATE Monte Carlo model for a newly developed small animal PET scanner: the IRI-microPET

Abstract Monte Carlo simulation is widely used in emission tomography, in order to assess image reconstruction algorithms and correction techniques, for system optimization, and study the parameters affecting the system performance. In the current study, the performance of the IRI-microPET system was simulated using the GATE Monte Carlo code and a number of performance parameters, including spatial resolution, scatter fraction, sensitivity, RMS contrast, and signal-to-noise ratio, evaluated and compared to the corresponding measured values. The results showed an excellent agreement between simulated and measured data: The experimental and simulated spatial resolutions (radial) for 18F in the center of the AFOV were 1.81 mm and 1.65 mm, respectively. The difference between the experimental and simulated sensitivities of the system was <7%. Simulated and experimental scatter fractions differed less than 9% for the mouse phantom in different timing windows. The validation study of the image quality indicated a good agreement in RMS contrast and signal-to-noise ratio. Also, system performance was compared with the two available commercial scanners which were simulated using GATE code. In conclusion, the assessment of the Monte Carlo modeling of the IRI-microPET system reveals that the GATE code is a flexible and accurate tool for describing the response of an animal PET system.

Contrast sensitivity in images of natural scenes

The contrast sensitivity function (CSF) characterizes spatial detection in the human visual system and is typically measured from simple, synthetic stimuli. We used spatial frequency decomposition, RMS contrast modulation, a yes/no paradigm and an adaptive staircase to measure isolated and contextual CSFs (iCSFs and cCSFs) from natural images. We employed Barten’s mechanistic model and adapted it for contextual modeling purposes by postulating that, signal detection in a given frequency band, when presented amongst other broadband signals, can be modeled as if amongst noise. We found that the iCSF varies with pictorial content, but that the standard CSF model and the image’s contrast spectrums are sufficient to predict with relative success the cCSF for any given image. We finally discuss the suitability of cCSF models in image quality modeling.

Curveball: A tool for rapid measurement of contrast sensitivity based on smooth eye movements.

The contrast sensitivity function (CSF) is an informative measure of visual function, but current tools for assessing it are limited by the attentional, motor, and communicative abilities of the participant. Impairments in these abilities can prevent participants from engaging with tasks or following an experimenter's instructions. Here, we describe an efficient new tool for measuring contrast sensitivity, Curveball, and empirically validate it with a sample of healthy adults. The Curveball algorithm continuously infers stimulus visibility through smooth eye tracking instead of perceptual report, and rapidly lowers stimulus contrast in real time until a threshold is found. The procedure requires minimal instruction to administer and takes only five minutes to estimate a full CSF, which is comparable to the best existing methods available for healthy adults. Task repeatability was high: the coefficients of repeatability were 0.275 (in log10 units of RMS contrast) within the same session and 0.227 across different days. We also present evidence that the task is robust across illumination changes, well correlated with results from conventional psychophysical methods, and highly sensitive to improvements in visual acuity from refractive correction. Our findings indicate that Curveball is a promising means of accurately assessing contrast sensitivity in previously neglected populations.

Pupil size is sensitive to dynamic change in scene layout properties

Previously we observed that pupil size is modulated by scene layout properties: smaller when viewing far or open scenes. Here we investigate whether changing direction of these properties, in addition to their static value, will also affect pupil size, by comparing pupillary response to otherwise identical scenes after exposure to scenes of different depths. 10 naive volunteers were instructed to free-view a series of 479 color video clips (mean duration ~8.57 s) in random order, while binocular pupil size was recorded using Eyelink 1000 eyetracker. All clips were extracted from documentary movies depicting natural or man-made sceneries, and were preprocessed to have roughly matched mean luminance and RMS contrast in each frame. Dominant depth of the scene in the clips was continuously rated by another group of 10 observers in separate sessions. Trials were sorted according to whether depth rating of preceding clip (adaptor) was farther, similar (served as baseline), or nearer compared with current clip (probe). Event-related pupil response time-locked to video onset was constructed for clips with at least one trial in all three conditions, and averaged across clips. When adaptor was farther, pupil size was significantly larger than baseline condition starting from as early as 280 ms, as if the probe was perceived nearer. The opposite was true when adapted to nearer scenes. Notably, larger difference in depth between adaptor and probe was significantly correlated with greater change in pupil size. Near reflex couldn't explain the result because it would predict opposite trend. In conclusion, the result suggests that pupil response is not only modulated by static value of scene layout properties, but also sensitive to their dynamic changes, probably due to high-level aftereffect in scene perception. Meeting abstract presented at VSS 2017

Electrophysiological Evaluation of Perceived Complexity in Streetscapes

AbstrctThis study represents an experimental research based on the electrophysiological evaluation of perceived complexity in streetscapes. Two physical measurements of perceived complexity, based on RMS contrast statistics and fractal information, were compared to human judgmental responses issued from brainwaves using Epoc Emotiv neuroheadset. The results indicated that frequency bands showed significant results in alpha and beta power bands in occipital and frontal electrodes, respectively. The higher the degree of familiarity with the streetscape image, the higher the degree of relaxation reflected by the increase of alpha power. Alpha power increased in dark streetscape images. RMS contrast statistics as well as fractal dimension values showed a positive correlation with beta band power associated with arousal and attention.

Design and performance evaluation of a high resolution IRI-microPET preclinical scanner

PET for small animal, IRI-microPET, was designed and built at the NSTRI. The scanner is made of four detectors positioned on a rotating gantry at a distance 50mm from the center. Each detector consists of a 10×10 crystal matrix of 2×2×10mm3 directly coupled to a PS-PMT. A position encoding circuit for specific PS-PMT has been designed, built and tested with a PD-MFS-2MS/s-8/14 data acquisition board. After implementing reconstruction algorithms (FBP, MLEM and SART) on sinograms, images quality and system performance were evaluated by energy resolution, timing resolution, spatial resolution, scatter fraction, sensitivity, RMS contrast and SNR parameters. The energy spectra were obtained for the crystals with an energy window of 300–700keV. The energy resolution in 511keV averaged over all modules, detectors, and crystals, was 23.5%. A timing resolution of 2.4ns FWHM obtained by coincidence timing spectrum was measured with crystal LYSO. The radial and tangential resolutions for 18F (1.15-mm inner diameter) at the center of the field of view were 1.81mm and 1.90mm, respectively. At a radial offset of 5mm, the FWHM values were 1.96 and 2.06mm. The system scatter fraction was 7.1% for the mouse phantom. The sensitivity was measured for different energy windows, leading to a sensitivity of 1.74% at the center of FOV. Also, images quality was evaluated by RMS contrast and SNR factors, and the results show that the reconstructed images by MLEM algorithm have the best RMS contrast, and SNR. The IRI-microPET presents high image resolution, low scatter fraction values and improved SNR for animal studies.

Does RMS contrast normalization impair coarse-to-fine processing of natural scenes?

Does RMS contrast normalization impair coarse-to-fine processing of natural scenes?