Human Visual Sensitivity Research Articles

Automatic Repeated-Loess Decomposition of Data Consisting of Sums of Oscillatory Curves

Repeated loess is a nonparametric procedure that uses progressive smoothing and differencing to decompose data consisting of sums of curves. Smoothing is by locally weighted polynomial regression. Here the procedure was developed so that the decomposition into components was controlled automatically by the number of maxima in each component. The level of smoothing of each component was chosen to maximize the estimated probability of the observed number of maxima. No assumptions were made about the periodicity of components and only very weak assumptions about their shapes. The automatic procedure was applied to simulated data and to experimental data on human visual sensitivity to line orientation.

ヒューマンインフォメーション 人間の視覚特性を総合的に考慮したＡＷＳＮＲの提案

An objective evaluation measure AWSNR that reflects human visual characteristics is proposed. In the measure, the spatial complexity of the original picture is determined from the fractal dimension, and the human visual sensitivity to the brightness of the picture is considered. Furthermore, subjective observation areas are predicted based on local complexity, local brightness, and the human spatial frequency characteristics. From experimental results using 350 pictures evaluated by 30 testers, it was found that the correlation coefficient between the MOS (Mean Opinion Score) and the proposed AWSNR became 0.91.

Human sensitivity to phase perturbations in natural images: a statistical framework.

Fourier-phase information is important in determining the appearance of natural scenes, but the structure of natural-image phase spectra is highly complex and difficult to relate directly to human perceptual processes. This problem is addressed by extending previous investigations of human visual sensitivity to the randomisation and quantisation of Fourier phase in natural images. The salience of the image changes induced by these physical processes is shown to depend critically on the nature of the original phase spectrum of each image, and the processes of randomisation and quantisation are shown to be perceptually equivalent provided that they shift image phase components by the same average amount. These results are explained by assuming that the visual system is sensitive to those phase-domain image changes which also alter certain global higher-order image statistics. This assumption may be used to place constraints on the likely nature of cortical processing: mechanisms which correlate the outputs of a bank of relative-phase-sensitive units are found to be consistent with the patterns of sensitivity reported here.

VQ Based on a Main Feature Classification in Images

A number of algorithms have been developed for lossy image compression. Among the existing techniques, a block-based scheme is widely used because of its tractability even for complex coding schemes. Fixed block-size coding, which is the simplest implementation of block-based schemes, suffers from the nonstationary nature of images. The formidable blocking artifacts always appear at low bit rates. To suppress this degradation, variable block-size coding is utilized. However, the allowable range of sizes is still limited because of complexity issues. By adaptively representing each region by its feature, input to the coder is transformed to fixed-size (8×8) blocks. This capability allows lower cross-correlation among the regions. Input feature is also classified into the proper group so that vector quantization can maximize its strength compatible with human visual sensitivity. Bit rate based on this algorithm is minimized with the new bit allocation algorithm. Simulation results show a similar performance in terms of PSNR over conventional discrete cosine transform in conjunction with classified vector quantization.

Error Diffusion of Clustered Dots

In this paper we show some experimental results on evaluating print quality of binarized images. We investigate how much the print quality is influenced by minimum dot size of a printer, binarization method, and human visual sensitivity. Especially, we propose an extended halftone screening algorithm. In this algorithm the total sum of errors in one block is distributed to the neighboring blocks.

A new image smoothing method based on a simple model of spatial processing in the early stages of human vision

The difficulty of preserving edges is central to the problem of smoothing images. The main problem is that of distinguishing between meaningful contours and noise, so that the image can be smoothed without loss of details. Substantial efforts have been devoted to solving this difficult problem, and a plethora of filtering methods have been proposed in the literature. Non-linear filters have proved to be more efficient than their linear counterparts. Here, a new nonlinear filter for noise smoothing is introduced. This filter is based on the psychophysical phenomenon of human visual contrast sensitivity. Results on real images are presented to demonstrate the validity of our approach compared to other known filtering methods.

Dependence of Print Quality on Minimum Dot Size and Binarization Method II

In this paper we show some experimental results about print quality of binarized images. We investigate how much it is influenced by minimum dot size of a printer, binarization method, and human visual sensitivity.

Characterization of human visual sensitivity for video imaging applications

Spatio-temporal pattern sensitivity has been studied by means of psychophysical tests on five subjects. The study has been undertaken to characterize human visual perception of typical coding artifacts of video sequences. The paper presents the experiments that have been carried out and the particular stimuli used for the study. The characteristics of human vision inferred from the experiments are used to parameterize a proposed spatio-temporal vision model.

A scene adaptive hybrid video coding scheme based on the LOT

Conventional standard video coding schemes based on independent coding of nonoverlapping image blocks produce undesirable effects (blocking effect and color bleeding, etc.) at low bit rate. A hybrid coding scheme evolving from the standard MPEG codec that combines lapped orthogonal transform (LOT) and overlapped block motion compensation and quantization approaches based on human visual system sensitivity is proposed to remove the artifacts. The LOT is applied to compress the resulting prediction errors of the overlapped motion compensation. The LOT coefficients are quantized by a dynamic intra/inter scene adaptive quantizer that is designed according to the human visual system and scene analysis to optimize the decoded image quality. This technique involves automatically deriving the most favorable quantizer matrix from the motion and scene analysis of image sequences and scaling the resulting matrix further by considering the buffer status. If a scene change is detected from the motion information, the proposed adaptive quantization can also help solve the difficulty of the buffer controller and maintain the picture quality as constant as possible. Performance of the proposed hybrid coding scheme with scene adaptive quantizer is demonstrated by computer simulations using standard test sequences and compared to that of the conventional MPEG-2 coding schemes. Subjective and objective tests show that image quality is improved considerably and the required bit rate is much less than that of the conventional method. Particularly, the image quality can be kept almost consistent, and the undesirable artifacts are reduced considerably.

Differential threshold of length and response criterion for inspecting irregular objects.

This research investigated human visual sensitivity and bias in inspecting irregular objects. A preliminary study was conducted using the method of constants to determine the threshold value for judgment of size. A factorial experiment was conducted using payoffs, rate of defective items, and detectability in the signal-detection theory as the factors. In total, eight experimental conditions were tested. 10 college students were recruited as subjects. Each subject was asked to compare 40 teapot shapes to a standard teapot shape under eight experimental conditions. Defective shapes were generated by lengthening the vertical dimension of a standard teapot shape by a factor of 1.01 and 1.04 for 'low' and 'high' detectability. The decision time and responses of 'identical' or 'different' were collected under all experimental conditions. Analysis indicates that the decision-making strategy used to inspect this irregular object was very close to maximizing the accuracy of decision-making by considering the rate of defective items. This result is different from most research findings in signal-detection theory in which responses of human beings are similar to degraded Bayes optimizers. The standard deviation of the signal distribution was about 1.30 and 1.41 times that of the noise distributions for 'low' and 'high' detectability.

Human Visual Sensitivity to Plumes with a Gaussian

This paper discusses results of a research project designed to develop an empirical model that could be used as a tool to predict human visual sensitivity to plumes. The resultant probability of detection algorithm (PROBDET) allows one to estimate the probability of a plume of known size, shape and contrast being detected visually. As a basis for the algorithm, a series of laboratory experiments using a high threshold signal detection procedure and computer generated images of plumes with Gaussian luminance distributions was conducted to measure human visual sensitivity to plumes. Results of the laboratory experiments are compared with results of contrast sensitivity experiments that examined visual sensitivity to stimuli with square and sine wave luminance distributions. An example of the PROBDET algorithm is presented to demonstrate its potential usefulness for assessing how probability of detection estimates change as plume size and contrast parameters vary. Since this research was designed to build on existing knowledge, a discussion of that knowledge and how it relates to the research conducted is also presented. The focus of this discussion is on the human visual system (HVS) and on how visual sensitivity is affected by factors such as the luminance of the stimulus and the surround, the luminance distribution of the stimulus, the size of the surround, and the size and spatial frequency characteristics of the stimulus.

多重解像度画像を用いた液晶ディスプレイ輝度むら欠陥検出

The visual inspection tool for detecting uneven area defects that appear in a screen of an LCD display by image processing was developed. By differential processing in multiple resolute images that are generated from an original image, various uneven area defects that have different sizes and shapes are detected. Evaluating factors that influence a human visual sensitivity about uneven area defects is experimented. As the experimental result, it was found that various factors about uneven area defects influence a visual conspicuous ratio. Through the inspection, various feature data related to a visual conspicuous ratio about uneven area defects were output.

Segmentation of gray-scale images using piecewise linear approximation

This paper deals with clock truncation coding for gray-scale images. An image region is segmented into unequal-sized square blocks according to local luminance variations and luminance values in the block are approximated by triangular plane patches constructed from the luminance values at the four vertices of the block. Computational complexities of the unequal-sized block segmentations are discussed. Segmentations are classified into three types: top-down splitting; bottom-up merging; and generalized split-and-merge method. It is derived from the theoretical model that initial block size in the split-and-merge method for a given image of size 256 × 256 is 17 × 17. Segmentation by accumulated square error is preferred to human visual sensitivity. Experimental results using a standard image have clarified that the segmentation by the accumulated square error improves the quality of approximated image to 1 to 2 dB compared with segmentation by the mean square error. Moreover, it is confirmed that the approximation by triangular plane patches is superior to JPEG for the compression of the images that have much flat areas.

A distortion measure for blocking artifacts in images based on human visual sensitivity

A visual model that gives a distortion measure for blocking artifacts in images is presented. Given the original and reproduced image as inputs, the model output is a numerical value that quantifies the visibility of blocking error in the reproduced image. The model is derived based on the human visual sensitivity to horizontal and vertical edge artifacts that result from blocking. Psychovisual experiments have been carried out to measure the visual sensitivity to these artifacts. In the experiments, typical edge artifacts are shown to subjects and the sensitivity to them is measured with the variation of background luminance, background activity, edge length, and edge amplitude. Synthetic test patterns are used as background images in the experiments. The sensitivity measures thus obtained are used to estimate the model parameters. The final model is tested on real images, and the results show that the error visibility predicted by the model correlates well with the subjective ranking.

Improved Chen-Smith image coder

A new transform coder based on the zonal sampling strategy, which outperforms the JPEG baseline coder with comparable computational complexity, is presented. The primary transform used is the 8- × 8-pixel-block discrete cosine transform, although it can be replaced by other transforms, such as the lapped orthogonal transform, without any change in the algorithm. This coder is originally based on the Chen-Smith coder, therefore, we call it an improved Chen-Smith (ICS) coder. However, because many new features were incorporated in this improved version, it largely outperforms its predecessor. Key approaches in the ICS coder, such as a new quantizer design, arithmetic coders, noninteger bit-rate allocation, decimated variance maps, distance-based block classification, and human visual sensitivity weighting, are essential for its high performance. Image compression programs were developed and applied to several test images. The results show that the ICS performs substantially better than the JPEG coder.

Digital images and human vision

Processing of digital images destined for visual consumption raises many interesting questions regarding human visual sensitivity. This talk will survey some of these questions, including some that have been answered and some that have not. There will be an emphasis upon visual masking, and a distinction will be drawn between masking due to contrast gain control processes, and due to processes such as hypothesis testing, pattern recognition, and visual search.

Models of contrast sensitivity in human vision

Eight models are examined as input-output representations of steady-state vision in humans at moderate to low level illumination. Three new models for visual contrast sensitivity are introduced and evaluated using contrast sensitivity function (CSF) data with samples on both narrow and wide frequency ranges. Additionally, five variations of previously published models are evaluated using the same data. A nonlinear least squares fitting algorithm produced the optimal parameters for each model. The eight models are compared on the basis of RMS error in their fit to the CSF data. The three new models, based on second-, third-, and fourth-order filter functions, provided the best fit to the data. They appear to more-closely approximate the underlying sensory mechanisms, and thus they provide a more useful input-output representation of the overall human visual system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

An objective method for the assessment of levelness of dyed materials

An objective method for the assessment of levelness of dyed materials has been established. The relative unlevelness index developed takes account of the coefficients of variation of reflectance measured over the visible spectrum, with appropriate consideration of human vision sensitivity. It was found that the index demonstrated good correlation with the visual levelness assessment.

Human visual sensitivity-weighted progressive image transmission using the lapped orthogonal transform

Progressive transmission of images based on the lapped orthogonal transform (LOT), adaptive classification, and human visual sensitivity (HVS) weighting is proposed. HVS weighting for LOT basis functions is developed. This technique is quite general and can be applied to any orthogonal transform. The method is compared with discrete cosine transform (DCT)-based progressive image transmission (PIT). It is shown that LOT-based PIT yields subjectively improved images compared to those based on DCT. This is consistent with the reduction in block structure characteristic of LOT image coding.

The Discriminability of Smooth Stereoscopic Surfaces

In this study the sensitivity of human vision to the smoothness of stereoscopic surface structure was investigated. In experiments 1 and 2 random-dot stereograms were used to evaluate the discrimination of smooth versus 'noisy' sinusoidal surfaces differing in the percentages of points on a single smooth surface. Fully coherent smooth surfaces were found to be much more discriminable than other less smooth randomly perturbed surfaces. In experiment 3 the discrimination between discontinuous triangle-wave surfaces and similarly shaped smoothly curved surfaces obtained from the addition of the fundamental and the third harmonic of the corresponding triangle-wave surface was evaluated. The triangle-wave surfaces were found to be more accurately discriminated from the smoothly curved surfaces than would be predicted from the detectability of the difference in their Fourier power spectra. This superior discriminability was attributed to differences between the curvature and/or discontinuity of the two surfaces. In experiment 3 the effects of incoherent 'noise' points on the discrimination between the two surface types were also evaluated. These randomly positioned noise points had a relatively small effect on the discrimination between the two surfaces. In general, the results of these experiments indicate that smooth surfaces are salient for stereopsis and that isolated local violations of smoothness are highly discriminable.