Human Visual System

The Fourier phase spectrum plays a central role regarding where in an image contours occur, thereby defining the spatial relationship between those structures in the overall scene. Only a handful of studies have demonstrated
psychophysically the relevance of the Fourier phase spectrum with respect to human visual processing, and none have demonstrated the relative amount of local cross-scale spatial phase alignment needed to perceptually
extract meaningful structure from an image. We investigated the relative amount of spatial phase alignment needed for humans to perceptually match natural scene image structures at three different spatial frequencies [3, 6, and 12 cycles per degree (cpd)] as a function of the number of structures within the image (i.e., “structural sparseness”). The results showed that (1) the amount of spatial phase alignment needed to match structures depends on structural sparseness, with a bias for matching structures at 6 cpd and (2) the ability to match partially phase-randomized images at a given spatial frequency is independent of structural sparseness at other spatial frequencies. The findings of the current study are discussed in terms of a network of feature integrators in the human visual system.

Two objects that project the same visual angle on the retina can appear to occupy very different proportions of the visual field if they are perceived to be at different distances. What happens to the retinotopic map in primary visual cortex (V1) during the perception of these size illusions? Here we show, using functional magnetic resonance imaging (fMRI), that the retinotopic representation of an object changes in accordance with its perceived angular size. A distant object that appears to occupy a larger portion of the visual field activates a larger area in V1 than an object of equal angular size that is perceived to be closer and smaller. These results demonstrate that the retinal size of an object and the depth information in a scene are combined early in the human visual system.

In this paper, we present an original image quality metric for open-loop transcoding architectures based on frequency selective transmission. The proposed metric computes the normalized HVS-weighted mean squared error (NWMSE) between the reference digital video compressed bitstream, and its transcoded version. This computation is performed directly from the quantized DCT coefficients of the compressed bitstream. The resulting MSE error is implicitly weighted by the HVS sensitivity by considering the MPEG perceptual coding properties. Finally, rate control and error propagation are also taken into account, in order to improve transcoded video quality assessment. Experimental results are given which show that the proposed NWMSE metric correlates well with a conventional WPSNR. This validates the proposed assumptions used for the NWMSE computation. The major advantage of the approach is its simplicity since it does not need to perform the complete decoding of the compressed bitstream. Hence, the NWMSE metric is highly suited for real-time video applications.

Several natural phenomena, such as mirages or the green flash, are owed to inhomogeneous media in which the index of refraction is not constant. This makes the light rays travel a curved path while going through those media. One way to simulate global illumination in inhomogeneous media is to use a curved ray tracing algorithm, but this approach presents some problems that still need to be solved. This paper introduces a full solution to the global illumination problem, based on what we have called curved photon mapping, that can be used to simulate several natural atmospheric phenomena. We also present a model of the Human Visual System (HVS) to display images in a more realistic way, taking into account how we perceive luminances in a real-world scene. This is of special interest in the green flash effect, where some of the perceived green is owed to bleaching of the photoreceptors in the human eye.

Image compression is a very important issue for several applications in the area of multimedia communications, the objective being reduction of storage and transmission costs. Many efficient coding techniques have been developed for various applications. Amongst them, the Joint Photographic Experts Group (JPEG) has been recommended for compression of continuous tone still images. However, the reconstructed images from JPEG compression produce annoying blocking artifacts near block boundaries, particularly in highly compressed images, because each block is transformed and quantized independently. Several techniques/algorithms have been proposed by researchers, both in spatial and frequency domains, for reduction of these artifacts with varied degree of success. These are briefly overviewed here. A new technique working in frequency domain, is proposed here by authors. This paper puts forth a method and an algorithm, working in frequency domain, for the detection and reduction of such blocking artifacts. These artifacts are modeled here as 2-D step functions between two neighboring blocks. Presence of the blocking artifacts is detected by using block activity based on human visual system (HVS) and block statistics. The boundary regions between blocks are identified as either smooth or non-smooth regions. The blocking artifacts in smooth regions are removed by modifying a few DCT coefficients appropriately, whilst an edge-preserving smoothing filter is applied to the non-smooth regions, i.e., genuine edges. The algorithm has been applied to variety of JPEG compressed images and results are compared with other postprocessing algorithms. The reduction in the blocking artifacts for each image have been evaluated using three indices, namely peak signal-to-noise ratio (PSNR), mean structure similarity (MSSIM) index based on human visual perception, and a new index, called here block boundary measure (BBM), applied

Digital watermarking has been proposed as a solution to the problem of copyright protection of multimedia data in a networked environment. It makes possible to tightly associate to a digital document a code allowing the identification of the data creator, owner, authorized consumer, and so on. In this paper a new watermarking algorithm for digital images is presented: the method, which operates in the frequency domain, embeds a pseudo-random sequence of real numbers in a selected set of DCT coefficients. After embedding, the watermark is adapted to the image by exploiting the masking characteristics of the human visual system, thus ensuring the watermark invisibility. By exploiting the statistical properties of the embedded sequence, the mark can be reliably extracted without resorting to the original uncorrupted image. Experimental results demonstrate that the watermark is robust to several signal processing techniques, including JPEG compression, low pass and median filtering, histogram equalization and stretching, dithering, addition of Gaussian noise, resizing, and multiple watermarking.

... stego data aiming at disrupting the watermark detection and of resolving copyrights, taking into account the statistics of the embedded watermark and exploiting features of the human visual system. In the second part of the paper we propose a “second generation benchmark”. ...

Tone-mapping operators are used to produce low dynamic range versions of the high dynamic range images, while preserving as much details as possible. We have proposed a tonemapping operator which is built on an existing histogram adjustment technique. It incorporates certain characteristics of the human visual system, to restrain the problem of extreme contrast enhancement of certain segments and intensive compression of others, associated with histogram equalization based techniques. Test results show significant improvement over traditional histogram adjustment. The proposed method also does quite well compared to the other state of the art tonemapping operators.

A new method to study the tuning of orientation detectors in the human visual system is proposed. The stimulus consists of a sequence of flashed sinusoidal gratings of random orientations and spatial phases shown at a fast presentation rate. The subject's task is to report, as fast as possible, when the presence of a particular orientation (horizontal, vertical, or oblique) is seen in the stimulus sequence by pressing a button. The data are analyzed by calculating the empirical distribution of orientations present in the stimulus sequence within an optimal time-window before the button was pressed. The resulting orientation distributions show a "Mexican hat" shape, which resembles the distributions obtained in some single neurons of monkey primary visual cortex using a similar method (Ringach et al., 1997). The findings are consistent with the idea of "lateral inhibition" between neighboring detectors in the orientation domain.

Abbreviations fMRI function magnetic resonance imaging I image description or feature p probability r reliability S object description V1 primary visual cortex Real-world statistics The statistical regularities in natural images and scene properties are essential for taming the complexity and ambiguity of image interpretation. For example, in

here it introduces an efficient multi-resolution watermarking methodology for copyright protection of digital images. By adapting the watermark signal to the wavelet coefficients, the proposed method is highly image adaptive and the watermark signal can be strengthen in the most significant parts of the image. As this property also increases the watermark visibility, usage of the human visual system is incorporated to prevent perceptual visibility of embedded watermark signal. Experimental results show that the proposed system preserves the image quality and is vulnerable against most common image processing distortions. Furthermore, the hierarchical nature of wavelet transform allows for detection of watermark at various resolutions, resulting in reduction of the computational load needed for watermark detection based on the noise level. The performance of the proposed system is shown to be superior to that of other available schemes reported in the literature.

A human visual system inspired process called foveation is an approach in managing the level of detail by controlling the region of interest. The scene is segmented according to the principles of our visual perception, modeling how the fovea behaves.

We present a method of recovering high dynamic range radiance maps from photographs taken with conventional imaging equipment. In our method, multiple photographs of the scene are taken with different amounts of exposure. Our algorithm uses these differently exposed photographs to recover the response function of the imaging process, up to factor of scale, using the assumption of reciprocity. With the known response function, the algorithm can fuse the multiple photographs into a single, high dynamic range radiance map whose pixel values are proportional to the true radiance values in the scene. We demonstrate our method on images acquired with both photochemical and digital imaging processes. We discuss how this work is applicable in many areas of computer graphics involving digitized photographs, including image-based modeling, image compositing, and image processing. Lastly, we demonstrate a few applications of having high dynamic range radiance maps, such as synthesizing realistic motion blur and simulating the response of the human visual system.

This paper summaries the state-of-the-art of image quality assessment (IQA) and human visual system (HVS). IQA provides an objective index or real value to measure the quality of the specified image. Since human beings are the ultimate receivers of visual information in practical applications, the most reliable IQA is to build a computational model to mimic the HVS. According to the properties and cognitive mechanism of the HVS, the available HVS-based IQA methods can be divided into two categories, i.e., bionics methods and engineering methods. This paper briefly introduces the basic theories and development histories of the above two kinds of HVS-based IQA methods. Finally, some promising research issues are pointed out in the end of the paper.

Human visual system makes an extensive use of visual attention in order to select the most relevant information and speed-up the vision process. Inspired by visual attention, several computer models have been developped and many computer vision applications rely today on such models. However, the actual algorithms are not suitable to omnidirectional images, which contain a significant amount of geometrical distorsion. In this paper, we present a novel computational approach that performs in spherical geometry and thus is suitable for omnidirectional images. Following one of the actual models of visual attention, the spherical saliency map is obtained by fusing together intensity, chromatic, and orientation spherical cue conspicuity maps that are themselves obtained through multiscale analysis on the sphere. Finally, the consecutive maxima in the spherical saliency map represent the spots of attention on the sphere. In the experimental part, the proposed method is then compared to the standard one using a synthetic image. Also, we provide examples of spots detection in real omnidirectional scenes which show its advantages. Finally, an experiment illustrates the homogeneity of the detected visual attention in omnidirectional images.

In this article, we discuss color theory and design with emphasis on use in statistical, scientific, and data visualization. Color theory is inextricably linked to the physiology of the human visual system, and color design is similarly inextricably linked to human perception. We discuss color perception in the human visual system. We then quantify color perception in terms of the Munsell System and the International Commission on Illumination (CIE) color space. We continue to discuss color design with a perspective on individuals with defective color perception and finally conclude with a discussion of color design for the use of color in presentations. 

The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed, and establishing new collaborations in these areas.

The structural similarity image quality paradigm is based on the assumption that the human visual system is highly adapted for extracting structural information from the scene, and therefore a measure of structural similarity can provide a good approximation to perceived image quality. This paper proposes a multi-scale structural similarity method, which supplies more flexibility than previous single-scale methods in incorporating the variations of viewing conditions. We develop an image synthesis method to calibrate the parameters that define the relative importance of different scales. Experimental comparisons demonstrate the effectiveness of the proposed method.

Head-worn display design is inherently an interdisciplinary subject fusing optical engineering, optical materials, optical coatings, electronics, manufacturing techniques, user interface design, computer science, human perception, and physiology for assessing these displays. This paper summarizes the state-of-the-art in head-worn display design (HWD) and development. This review is focused on the optical engineering aspects, divided into different sections to explore principles and applications. Building on the guiding fundamentals of optical design and engineering, the principles section includes a summary of microdisplay or laser sources, the Lagrange invariant for understanding the trade-offs in optical design of HWDs, modes of image presentation (i.e., monocular, biocular, and stereo) and operational modes such as optical and video see-through. A brief summary of the human visual system pertinent to the design of HWDs is provided. Two optical design forms, namely, pupil forming and non-pupil forming are discussed. We summarize the results from previous design work using aspheric, diffractive, or holographic elements to achieve compact and lightweight systems.

The network provides a method of communication to distribute information to the masses. With the growth of data communication over computer network, the security of information has become a major issue. Steganography and cryptography are two different data hiding techniques. Steganography hides messages inside some other digital media. Cryptography, on the other hand obscures the content of the message. We propose a high capacity data embedding approach by the combination of Steganography and cryptography. In the process a message is first encrypted using transposition cipher method and then the encrypted message is embedded inside an image using LSB insertion method. The combination of these two methods will enhance the security of the data embedded. This combinational methodology will satisfy the requirements such as capacity, security and robustness for secure data transmission over an open channel. A comparative analysis is made to demonstrate the effectiveness of the proposed method by computing Mean square error (MSE) and Peak Signal to Noise Ratio (PSNR). We analyzed the data hiding technique using the image performance parameters like Entropy, Mean and Standard Deviation. The stego images are tested by transmitting them and the embedded data are successfully extracted by the receiver. The main objective in this paper is to provide resistance against visual and statistical attacks as well as high capacity.

Attention is an integral part of the human visual system and has been widely studied in the visual attention literature. The human eyes fixate at important locations in the scene, and every fixation point lies inside a particular region of arbitrary shape and size, which can either be an entire object or a part of it. Using that fixation point as an identification marker on the object, we propose a method to segment the object of interest by finding the "optimal" closed contour around the fixation point in the polar space, avoiding the perennial problem of scale in the Cartesian space. The proposed segmentation process is carried out in two separate steps: First, all visual cues are combined to generate the probabilistic boundary edge map of the scene; second, in this edge map, the "optimal" closed contour around a given fixation point is found. Having two separate steps also makes it possible to establish a simple feedback between the mid-level cue (regions) and the low-level visual cues (edges). In fact, we propose a segmentation refinement process based on such a feedback process. Finally, our experiments show the promise of the proposed method as an automatic segmentation framework for a general purpose visual system.

The dynamic range of a camera is much lesser than that of human visual system. This causes images taken by the camera to look different from how the scene would have looked to a naked eye. Multi Scale Retinex with Color Restoration(MSRCR) algorithm enhances images taken under a wide range of nonlinear illumination conditions to the level that a user would have perceived it in real time. But there are parameters used in this enhancement method that are image dependent and have to be varied based on the images under consideration. In this paper we propose a completely automated approach for MSRCR by obtaining parameter values from the image being enhanced.

In this work we present a new algorithm for digital images unsupervised enhancement with simultaneous global and local effects, called ACE for Automatic Color Equalization. It is based on a computational model of the human visual system that merges the two basic ''Gray World'' and ''White Patch'' global equalization mechanisms. Inspired by some adaptation mechanisms of the human vision, it realizes a local filtering effect by taking into account the color spatial distribution in the image. Like the human visual system, ACE is able to ''adapt'' to widely varying lighting conditions and to extract visual information from the environment efficaciously. It has shown promising results in achieving different equalization tasks, e.g. performing color and lightness constancy, realizing image dynamic data driven stretching, controlling the contrast. Characteristics, tests and results are presented.

Color equalization algorithms exhibit a variety of behaviors described in two differing types of models: Gray World and White Patch. These two models are considered alternatives to each other in methods of color correction. They are the basis for two human visual adaptation mechanisms: Lightness Constancy and Color Constancy. The Gray World approach is typical of the Lightness Constancy adaptation because it centers the histogram dynamic, working the same way as the exposure control on a camera. Alternatively, the White Patch approach is typical of the Color Constancy adaptation, searching for the lightest patch to use as a white reference similar to how the human visual system does. The Retinex algorithm basically belongs to the White Patch family due to its reset mechanism. Searching for a way to merge these two approaches, we have developed a new chromatic correction algorithm, called Automatic Color Equalization (ACE), which is able to perform Color Constancy even if based on Gray World approach. It maintains the main Retinex idea that the color sensation derives from the comparison of the spectral lightness values across the image. We tested different performance measures on ACE, Retinex and other equalization algorithms. The results of this comparison are presented.

Why do we have colour? What use is it to us? Some of the obvious answers are that we see colour so that we can recognise objects, spot objects more quickly, tell when fruit is ripe or rotten. These reasons make a lot of sense, but are there others? In this paper, we explore the things that colour makes easier for computational vision systems. In particular, we examine the role of colour in understanding specularities, processing interreflections, identifiying metals from plastics and wet surfaces from dry ones, choosing foveation points, disambiguating stereo matches, discriminating textures and identifying objects. Of course, what is easier for a computational vision system is not necessarily the same for the human visual system but it can perhaps help us create some hypotheses about the role of colour in human perception. We also consider the role of colour constancy in terms of whether or not it is required for colour to be useful to a computer vision system.

Face recognition is nowadays one of the most challenging biometric modalities for the identification of individuals. In the last two decades several experimental as well as commercial systems have been developed exploiting different physical properties of the face image. Either being based on processing 2D or 3D information all these methods perform a face classification of the individuals based on some relevant features extracted from the raw image data. The data acquisition, preprocessing and the feature extraction/selection are all topics of the greatest importance to design a good performing recognition system. At the same time, the right choice of the features to be used as the basis for the face representation, which must be based on the uniqueness of such features, as well as most advanced issues such as the incorporation of quality information and the cope for ageing effects, are all of paramount importance.

A novel data hiding scheme, denoted as unseen visible watermarking (UVW), is proposed. In UVW schemes, hidden information can be embedded covertly and then directly extracted using the human visual system as long as appropriate operations (e.g., gamma correction provided by almost all display devices or changes in viewing angles relative to LCD monitors) are performed. UVW eliminates the requirement of invisible watermarking that specific watermark extractors must be deployed to the receiving end in advance, and it can be integrated with 2-D barcodes to transmit machine-readable information that conventional visible watermarking schemes fail to deliver. We also adopt visual cryptographic techniques to guard the security of hidden information and, at the same time, increase the practical value of visual cryptography. Since UVW can be alternatively viewed as a mechanism for visualizing patterns hidden with least-significant-bit embedding, its security against statistical steganalysis is proved by empirical tests. Limitations and other potential extensions of UVW are also addressed.

This paper presents a new formulation of the regularized image up-sampling problem that incorporates models of the image acquisition and display processes. We give a new analytic perspective that justifies the use of total-variation regularization from a signal processing perspective, based on an analysis that specifies the requirements of edge-directed filtering. This approach leads to a new data fidelity term that has been coupled with a total-variation regularizer to yield our objective function. This objective function is minimized using a level-sets motion that is based on the level-set method, with two types of motion that interact simultaneously. A new choice of these motions leads to a stable solution scheme that has a unique minimum. One aspect of the human visual system, perceptual uniformity, is treated in accordance with the linear nature of the data fidelity term. The method was implemented and has been verified to provide improved results, yielding crisp edges without introducing ringing or other artifacts.

This paper presents a novel approach of adaptive visual tuning of a watermark in Discrete Cosine Transform (DCT) domain. The proposed approach intelligently selects appropriate frequency bands as well as optimal strength of alteration. Genetic Programming (GP) is applied to structure the watermark by exploiting both the characteristics of human visual system and information pertaining to a cascade of conceivable attacks. The developed visual tuning expressions are dependent on frequency and luminance sensitivities, and contrast masking. To further enhance robustness, spread spectrum based watermarking and Bose-Chadhuri-Hocquenghem (BCH) coding is employed. The combination of spread spectrum sequence, BCH coding and GP based non-linear structuring makes it extremely difficult for an attacker to gain information about the secret knowledge of the watermarking system. Experimental results show the superiority of the proposed approach against the existing approaches. Especially, the margin of improvement in robustness will be of high importance in medical and context aware related applications of watermarking. ß

Boundary detection constitutes a crucial step in many computer vision tasks. We present a novel learning approach to automatically construct a boundary detector for natural images via Genetic Programming (GP). Our approach aims to use GP as a learning framework for evolving computer programs that are evaluated against human-marked boundary maps, in order to accurately detect and localize boundaries in natural images. Our GP system is unique in that it combines filter kernels that were inspired by models of processing in the early stages of the primate visual system, but makes no assumption about what constitutes a boundary, thus avoiding the need to make ad-hoc intuitive definitions. By testing the evolved boundary detectors on a benchmark set of natural images with associated human-marked boundaries, we show performance to be quantitatively competitive with existing computervision approaches. Moreover, we show that our evolved detector provides insights into the mechanisms underlying boundary detection in the human visual system.

Computer generated images by default render the entire scene in perfect focus. Both camera optics and the human visual system have limited depth of field, due to the finite aperture or pupil of the optical system. For more realistic computer graphics as well as to enable artistic control over what is and what is not in focus, it is desirable to add depth of field blurring. Starting with the work of Potmesil and Chakravarty [34], there have been numerous approaches to adding depth of field effects to computer graphics. Published work in depth of field for computer graphics has been previously surveyed by Barsky [2][3]. Later, interactive depth of field techniques were surveyed by Demers . Subsequent to these surveys, however, there have been important developments. This paper surveys depth of field approaches in computer graphics, from its introduction to the current state of the art. Figure 1: (left) Image before and after depth of field has been added via postprocessing (courtesy of Indranil Chakravarty [33]). (right) A dragon scene rendered with a distributed ray tracing approach (courtesy of Magnus Strengert [23]).

Abstract—By taking into account the properties and limitations of the human visual system (HVS), images can be more efficiently compressed, colors more accurately reproduced, prints better rendered, to mention a few major advantages. To achieve these goals it is necessary to build a computational model of the HVS. In this paper we give an introduction to the general issue of HVS-modeling and review the specific applications of visual quality assessment and HVS-based image compression, which are closely related. On one hand, ...

The present paper reflects a work in progress toward a definition of circadian light, one that should be informed by the thoughtful, century-old evolution of our present definition of light as a stimulus for the human visual system. This work in progress is based upon the functional relationship between optical radiation and its effects on nocturnal melatonin suppression, in large part because the basic data are available in the literature. Discussed here are the fundamental differences between responses by the visual and circadian systems to optical radiation. Brief reviews of photometry, colorimetry, and brightness perception are presented as a foundation for the discussion of circadian light. Finally, circadian light (CL A ) and circadian stimulus (CS) calculation procedures based on a published mathematical model of human circadian phototransduction are presented with an example.

Visual information can in principle be dynamically optimised by monitoring the user’s state of attention, e.g. by tracking eye movements. Gaze directed displays are therefore an important enabling technology for attention aware systems. We present a state-of-the-art review of both (1) techniques to register the direction of gaze and (2) display techniques that can be used to optimally adjust visual information presentation to the capabilities of the human visual system and the momentary direction of viewing. We focus particularly on evaluation studies that were performed to assess the added value of these displays. We identify promising application areas and directions for further research.

A multi-color dithering algorithm is proposed, which converts a barycentric combination of color intensities into a multi-color nonoverlapping surface coverage. Multi-color dithering is a generalization of standard bi-level dithering. Combined with tetrahedral color separation, multi-color dithering makes it possible to print images made of a set of non-standard inks. In contrast to most previous color halftoning methods, multi-color dithering ensures by construction that the different selected basic colors are printed side by side. Multi-color dithering is applied to generate color images whose screen dots are made of artistic shapes (letters, symbols, ornaments, etc.). Two dither matrix postprocessing techniques are developed, one for enhancing the visibility of screen motives and one for the local equilibration of large dither matrices. The dither matrix equilibration process corrects disturbing local intensity variations by taking dot gain and the human visual system transfer function into account. Thanks to the combination of the presented techniques, high quality images can be produced, which incorporate at the micro level the desired artistic screens and at the macro level the full color image. Applications include designs for advertisements and posters as well as security printing. Multi-color dithering also offers new perspectives for printing with special inks, such as fluorescent and metallic inks.

Computer generated images by default render the entire scene in perfect focus. Both camera optics and the human visual system have limited depth of field, due to the finite aperture or pupil of the optical system. For more realistic computer graphics as well as to enable artistic control over what is and what is not in focus, it is desirable to add depth of field blurring. Starting with the work of Potmesil and Chakravarty[33][34], there have been numerous approaches to adding depth of field effects to computer graphics. Published work in depth of field for computer graphics has been previously surveyed by Barsky [2][3]. Later, interactive depth of field techniques were surveyed by Demers [12]. Subsequent to these surveys, however, there have been important developments. This paper surveys depth of field approaches in computer graphics, from its introduction to the current state of the art. Figure 1: (left) Image before and after depth of field has been added via postprocessing (cou...

We present a comparison between two color equalization algorithms: Retinex, the famous model due to Land and Mc-Cann, and Automatic Color Equalization (ACE), a new algorithm recently presented by the authors. These two algorithms share a common approach to color equalization, but different computational models. We introduce the two models focusing on differences and common points. An analysis of their computational characteristics illustrates the way the Retinex approach has influenced ACE structure, and which aspects of the first algorithm have been modified in the second one and how. Their interesting equalization properties, like lightness and color constancy, image dynamic stretching, global and local filtering, and data driven dequantization, are qualitatively and quantitatively presented and compared, together with their ability to mimic the human visual system.