Intraocular scattering can become an important source of optical degradation in the aging eye. To evaluate its relative contribution to the ocular modulation transfer function (MTF), a compact, dual experimental system comprising a laser ray tracing (LRT) wavefront sensor and a double-pass setup is used. An aberrometric MTF is estimated from aberration measurements, whereas a second MTF is derived from the double-pass point-spread function. While the former only accounts for the effect of aberrations (up to seventh order), the double-pass MTF includes the combined effect of both scattering and aberrations. A 532-nm laser light source is used to minimize choroidal scattering. Measurements are done on 19 normal, healthy eyes from three groups of subjects of different ages. The two MTFs are obtained for a 6-mm pupil diameter and partial refractive compensation. Intraocular scattering is modeled as a random wavefront aberration characterized by its variance and correlation length. These parameters are fitted from the differences between both MTFs. Our results show that double-pass and LRT techniques provide similar MTFs for most normal eyes, although small amounts of scattering, or high-order aberrations, could be measured in some eyes. A gradual increase in intraocular scattering with age is also observed.
Three basic stages towards the global modeling of the eye are presented. In the first stage, an adequate choice of the basis geometrical model, general ellipsoid in this case, permits, to fit in a natural way the typical "melon" shape of the cornea with minimum complexity. In addition it facilitates to extract most of its optically relevant parameters, such as the position and orientation of it optical axis in the 3D space, the paraxial and overall refractive power, the amount and axis of astigmatism, etc. In the second level, this geometrical model, along with optical design and optimization tools, is applied to build customized optical models of individual eyes, able to reproduce the measured wave aberration with high fidelity. Finally, we put together a sequence of schematic, but functionally realistic models of the different stages of image acquisition, coding and analysis in the visual system, along with a probabilistic Bayesian maximum a posteriori identification approach. This permitted us to build a realistic simulation of the all the essential processes involved in a visual acuity clinical exam. It is remarkable that at all three levels, it has been possible for the models to predict the experimental data with high accuracy.
Corneal topography has shown to be an essential tool in the ophthalmology clinic both in diagnosis and custom treatments (refractive surgery, keratoplastia), having also a strong potential in optometry. The post processing and analysis of corneal elevation, or local curvature data, is a necessary step to refine the data and also to extract relevant information for the clinician. In this context a parametric cornea model is proposed consisting of a surface described mathematically by two terms: one general ellipsoid corresponding to a regular base surface, expressed by a general quadric term located at an arbitrary position and free orientation in 3D space and a second term, described by a Zernike polynomial expansion, which accounts for irregularities and departures from the basic geometry. The model has been validated obtaining better adjustment of experimental data than other previous models. Among other potential applications, here we present the determination of the optical axis of the cornea by transforming the general quadric to its canonical form. This has permitted us to perform 3D registration of corneal topographical maps to improve the signal-to-noise ratio. Other basic and clinical applications are also explored.
The rapid development of cataract and refractive surgery requires new methods to assess the optical quality of the eye. The optimized optical design of custom treatments to improve the optical performance of individual eyes requires, at least, to have the technology to (1) measure the geometry (anatomy) of the optics of the eye; (2) measure the optical performance (refractive state, aberrations, etc); (3) Build a custom optical and anatomical model of the individual eye to treat; (4) Optimal design of custom treatments. In this communication we will present the work carried out by our group to develop methods for measuring and modeling the optical performance of the eye. In particular, we will focus, first, on the Laser Ray Tracing method that we have developed to measure the optical aberrations of the eye, as a physical in vivo implementation of the classical numerical ray tracing used by optical designers; and second, on the development of custom optical models of the eye to perform that numerical ray tracing which predicts with a high fidelity experimental measurements. The methods developed have been applied to design both custom surgery and optical aids to improve optical performance.
A method to predict visual acuity in individual eyes has been developed, which combines realistic optical and neural models of early visual processing. Visual acuity is usually obtained as the outcome of a pattern recognition task. However, since the human eye is highly aberrated, standard pattern recognition methods can not be used here, because they fail severely in the presence of optical aberrations, contrarily to what we observe in the human visual system. Here, we have applied a pattern recognition method invariant against optical aberrations, based on early visual models. The results obtained in several real cases provided accurate and realistic predictions of visual acuity. (Summary only available)
Current models of primary visual cortex (V1) include a linear filtering stage followed by a gain control mechanism that explains some of the nonlinear behavior of neurons. The nonlinear stage has been modeled as a divisive normalization in which each input linear response is half-rectified, squared and then divided by a weighted sum of half-rectified and squared linear responses in a certain neighborhood. Recently, Simoncelli and colleagues have suggested that this normalization reduces the statistical dependence of neuron responses. In this communication, we present an efficient implementation of these ideas as a practical image representation, and suggest some applications. The linear stage is implemented as a four-level orthogonal wavelet decomposition based on Daubechies filters, and the nonlinear normalization stage uses an improved version of Simoncelli's scheme. The normalization parameters are adapted to minimize statistical dependence between the output responses, so that the resulting representation consists of a set of statistically independent features or visual events. Since both linear and non-linear transforms applied can be inverted, this representation can be highly useful in different applications.
New objective methods to measure the optical aberrations of the eye are reviewed, in particular probably more representative ones: Hartmann-Shack wavefront sensor and Laser Ray Tracing. They are shown to be robust and provide highly reliable data, which is permitting to obtain many new results about the optics of the eye in basic and clinical studies. In addition, different experiments have demonstrated the correction of eye's aberration. Again tow representative approaches are reviewed. The first results were obtained with the close-loop adaptive optics system developed at the University of Rochester. Later on, phase plates made by photo sculpture in photoresist, have also permitted the correction of ocular aberrations. This is a new, but already very active field of research, which has opened many new questions and a wide variety of applications.
This communication reviews some recent studies on the optical performance of the human eye. Although the retinal image cannot be recorded directly, different objective methods have been developed, which permit to determine optical quality parameters, such as the Point Spread Function (PSF), the Modulation Transfer Function (MTF), the geometrical ray aberrations or the wavefront distortions, in the living human eye. These methods have been applied in both basic and applied research. This includes the measurement of the optical performance of the eye across visual field, the optical quality of eyes with intraocular lens implants, the aberrations induced by LASIK refractive surgery, or the manufacture of customized phase plates to compensate the wavefront aberration in the eye.
This paper explains the methodology and results of research on the growth of large forest fires, using information from the NOAA-AVHRR sensor. Numerous algorithms have been developed for discriminating pixels of active fires from the rest. These can be divided into three groups: a) those based on information from channel 3 (single channel); b) those using algorithms from several channels (multi-channel); c) those that, as well as using this information, compare the pixel with those around it (contextual). This research used the contextual algorithm of Flasse and Ceccato1 to discriminate between pixels corresponding to active fires and the rest, and to interpret the growth of the fire. Two fires were selected for the purpose: those in the Sierra de Cazulas (Granada) in August 1999, and in Valencia, in July 1994. The results provided useftil information on the growth of fire in general, the area, speed at which it spread and prevailing direction. This suggests that this method can be recommended for studies on fire behaviour, as well as in the provision of resources for fighting the fire at both the regional and national level.
Francisco Meca Meca, Francisco Rodriguez Sanchez, Manuel Mazo Quintas, Juan Garcia Dominguez, Rafael Fonolla Navarro, Eduardo Sebastian Martinez, Jose Jimenez Calvo, Diego Lillo Rodriguez, Miguel Garcia Garrido
Wheels, hubs and brake discs in a train during its circulation are under mechanical strains that make its temperature increase above the environment temperature. Mechanical defects in those elements produce an excessive friction and, as a consequence of it, an important increment of its temperature in relation to normal values. Detecting these anomalies is essential to avoid accidents and it is performed by fixed systems located next to rails which make infrared temperature measurements of hot points and send them to a supervisory station that takes the proper steps. The paper introduces the most important problems which must be dealt with during the designing stage of the measurement system. It also explains the solutions taken by the authors in order to assure the minimum operative aims demanded by the application. These problems includes: the choice of the detector and measurement method, communication with the supervisory station, and the environment conditions. Finally, the research lines followed by the authors in order to improve and extend the system's capabilities are explained.
The paper formation is one of the most important properties of the paper but remains a difficult property to determine. A method for determining this property has been developed. This method based on light transmission image analysis uses the power spectra of the Fourier transform to analyze the floc distribution. The method has been tested for various furnishes and allows a well discrimination between different qualities of formation that does the standard formation number.
This communication reviews some classic and recent studies of the optical performance of the human eye across visual field. Although the retinal image can not be recorded directly, different objective methods have been developed, which permit to determine optical quality parameters, such as the Point Spread Function, the Modulation Transfer Function, the geometrical ray aberrations or the wavefront distortions, in the living human eye. Experimental data obtained with these methods, along with a more exact knowledge of the anatomy (asphericities) of the optical surfaces of the eye, permit us to build more accurate models of the optical system of the eye, learn about its wide-angle optical design, and develop applications.
Various techniques based on image processing are presented for the automatic quality control of textiles. General defects (shrinking, abrasion, etc.) are detected by using operations in the frequency domain. Local defects (broken threads, mispicks, double yarns, etc.) are detected using a method based on a multiscale and multiorientation Gabor scheme that imitates the visual coding in early human vision. Also pilling resistance is automatically evaluated in wear-and-tear fabrics by a new algorithm which combines operations in both the spatial and frequency domain.
In this work we summarize some of the work of our team in the last years, devoted to the use of spatial light modulators (SLM) in optical correlators and optical image processors. We have built an optical processor that uses two liquid crystal SLMs, one to implement the image to be processed and a second one to implement a Fourier filter. We analyzed the advantages of the use of SLMs, but also the restrictions they impose. We proposed several architectures and filters design to take profit of this SLM based optical processor.
Directional filters are not normally used as pre-filters for optical flow estimation because orientation selectivity tends to increase the aperture problem. Despite this fact, here we apply a subband decomposition using directional spatio-temporal filters at different resolution to discriminate multiple motions at the same location. We first obtain multiple estimates of the velocity by applying the classic gradient constraint to the output of each filter. Spatio-temporal gradients of GD2 channel response are easily obtained as linear combinations of the set of 10 separable GD3 channel responses, which constitutes a multipurpose scheme for visual representation of image sequences. Then, we obtain an overdetermined linear system by imposing local constant velocity. This system is solved by least-squares yielding an estimate of the velocity and its covariance matrix. After segmenting the resulting 6 X 3 velocity estimates we combine them using Bayesian probability rules. Segmentation maintains the ability to represent multiple motions, while the combination of estimates reduces the aperture problem. Results for synthetic and real sequences are highly satisfactory. Mean errors in complex standard sequences are below those provided by most published methods.
Automatic object segmentation in highly noisy image sequences, composed by a translating object over a background having a different motion, is achieved through joint motion-texture analysis. Local motion and/or texture is characterized by the energy of the local spatio-temporal spectrum, as different textures undergoing different translational motions display distinctive features in their 3D (x,y,t) spectra. Measurements of local spectrum energy are obtained using a bank of directional 3rd order Gaussian derivative filters in a multiresolution pyramid in space- time (10 directions, 3 resolution levels). These 30 energy measurements form a feature vector describing texture-motion for every pixel in the sequence. To improve discrimination capability and reduce computational cost, we automatically select those 4 features (channels) that best discriminate object from background, under the assumptions that the object is smaller than the background and has a different velocity or texture. In this way we reject features irrelevant or dominated by noise, that could yield wrong segmentation results. This method has been successfully applied to sequences with extremely low visibility and for objects that are even invisible for the eye in absence of motion.
In this work we demonstrate the relationship existing between two important issues in vision: multi-scale local spectrum analysis, and log-polar foveatization. We show that, when applying a continuous set of self-similar (rotated and scaled) band-pass filters to estimate the local spectrum at a given point of attention of the image, the inverse Fourier transform of this local spectrum is a log- polar foveated version of the original image at that position. Both the local spectrum and its associated foveated image can be obtained through log-polar warping of the spectral/spatial domain followed by a conventional invariant low-pass filtering and the corresponding inverse warping. Furthermore, the low-pass filters in the warped space and frequency domains are mirror versions of each other. Thus, filters with mirror symmetry under the log- polar warping are self-dual, and make the foveatization process commute with the Fourier transform. Nevertheless, in order to implement a fovea that can be easily moved across the image, it is preferable to use a fixed bank of steerable filters, instead of applying log-polar warpings with different centers. Using low-pass scalable filters we have implemented a real-time moving fovea. We believe that a dual finite spatial/spectral local representation of images could be a very powerful tool for many visual tasks, which could benefit from a dual explicit representation in space and spatial frequency, as well as from the rotation and scale invariance naturally achieved in both domains.
Wear and tear generate fluffiness and pills that remain in the web surface spoiling the appearance of a fabric. In quality control of textiles it is necessary to have an objective method to measure pilling that improves current methods based on visual estimations of the degree of pilling. In this work we optimize a method for piling evaluation based on image analysis that we proposed recently. The method combined operations in both the frequency and the spatial domains in order to better segment pills from the textured web background. We considered a logarithmic in base two relationship between the area of pilling and the degree of pilling based on the human perception mechanisms.
Gabor functions, which localize information in both the spatial and the frequency domains, are used as filters for the inspection of common local defects in textile webs. A variety of defects are analyzed in different fabrics and in every case the flaws are finally segmented from the background.
One problem in the quality control of textiles is the measure of the pilling degree in worn fabrics. Wear and tear make some fibers separate from the woven yarns and get entangled in pills distributed on the web. Pilling degree is often evaluated by experts from a visual comparison with standard images. In this work, we use some techniques of digital image processing to evaluate the pilling degree. From the analysis of a set of standard images we establish and develop a sequential method for an objective measurement. The method involves operations in the frequency domain as well as in the spatial domain. In the final processed images we segment pills from the background fabric and we measure the total area of pilling for each image. We have verified that there is a logarithmic relationship between the total pilling area and the degree of pilling.
We propose a new texture synthesis-by-analysis method inspired by current models of biological early vision and based on a multiscale Gabor scheme. The analysis stage starts with a log-polar sampling of the estimated power spectral density of the texture by a set of 4 by 4 Gabor filters, plus a low-pass residual (LPR). Then, for each channel, we compute its energy and its two (X,Y) bandwidths. The LPR is coded by five parameters. In addition, the density function of the original texture is also estimated and compressed to sixteen values. Therefore, texture is coded by only 69 parameters. The synthesis method consists of generating a set of 4 by 4 synthetic channels (Gabor filtered noise signals). Their energies and bandwidths are corrected to match the original features. These bandpass filtered noise signals are mixed into a single image. Finally, the histogram and LPR frequencies of the resulting texture are modified to fit the original values. We have obtained very satisfactory results both with highly random textures and with some quasi-periodic textures. Compared to previous methods, ours has other important advantages: high robustness (stable, non iterative and fully automatic), high compactness of the coding, and computational efficiency.
We have developed a robust method for image segmentation based on a local multiscale texture description. We first apply a set of 4 by 4 complex Gabor filters, plus a low-pass residual (LPR), producing a log-polar sampling of the frequency domain. Contrary to other analysis methods, our Gabor scheme produces a visually complete multipurpose representation of the image, so that it can also be applied to coding, synthesis, etc. Our sixteen texture features consist of local contrast descriptors, obtained by dividing the modulus of the response of the complex Gabor filter by that of the LPR at each location. Contrast descriptors are basically independent of slow variations in intensity, while increasing the robustness and invariance of the representation. Before applying the segmentation algorithm, we equalize the number of samples of the four layers in the resulting pyramid of local contrast descriptors. This method has been applied to segmentation of electron microscopy images, obtaining very good results in this real case, where robustness is a basic requirement, because intensity, textures and other factors are not completely homogeneous.
In this work we apply a pyramidal Gabor image decomposition to pattern recognition. The recognition process is based on a multichannel correlation. The filter is adapted in each channel to the corresponding decomposition of the object to be recognized. The results obtained with the multichannel process are compared with those obtained by using the classical matched filter (CMF) and phase only filter (POF).
We have developed a new technique for the objective determination of the cone spacing in the living human fovea, and obtained direct measurements of the distance between cones at retinal eccentricities ranging from 0 to 1 deg. The method is similar to stellar speckle interferometry, and consists of recording a series of short-exposure images of small foveal patches, illuminated by a laser spot. Each individual image presents a speckle pattern, correlated with the topography of the cone mosaic, and contains spatial frequency information up to the diffraction limit of the optical system of the eye. The cone spacing is measured in the spatial domain, as the reciprocal of the radius of the ring present in the average power spectrum. The results obtained are in close agreement with estimates based on microscopy of excised fovea, with psychophysical measurements, and with recent results obtained with another high resolution imaging technique outside the center of the fovea.
A double-pass method is applied to determine the retinal image quality of eyes implanted with intraocular lenses (IOLs). The effect of focus on image quality was measured in two groups of patients that had been implanted with either monofocal or multifocal IOLs. The results show that the overall retinal image quality is reduced in eyes with multifocal lenses with respect to that implanted with monofocal IOLs. Although the depth of focus is larger in multifocal lOLs (4 to 5 D) than in the monofocal IOLs (2 to 3 D), some patients implanted with monofocal IOLs have higher image quality than those implanted with multifocal IOLs in a range of about 4 D around the best focus. In eyes implanted with monofocal IOLs, astigmatism plays a major role to reduce the retinal contrast, but also increases the depth of focus. These "in vivo" measurements show that there is considerable variability in image quality among individuals with the same type of monofocal IOLs. The main factors causing this variability seem to be age and astigmatism produced by surgery.
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