Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times, from different sensors, or from different viewpoints. Virtually all large systems which evaluate images require the registration of images, or a closely related operation, as an intermediate step. Specific examples of systems where image registration is a significant component include matching a target with a real-time image of a scene for target recognition, monitoring global land usage using satellite images, matching stereo images to recover shape for autonomous navigation, and aligning images from different medical modalities for diagnosis.Over the years, a broad range of techniques has been developed for various types of data and problems. These techniques have been independently studied for several different applications, resulting in a large body of research. This paper organizes this material by establishing the relationship between the variations in the images and the type of registration techniques which can most appropriately be applied. Three major types of variations are distinguished. The first type are the variations due to the differences in acquisition which cause the images to be misaligned. To register images, a spatial transformation is found which will remove these variations. The class of transformations which must be searched to find the optimal transformation is determined by knowledge about the variations of this type. The transformation class in turn influences the general technique that should be taken. The second type of variations are those which are also due to differences in acquisition, but cannot be modeled easily such as lighting and atmospheric conditions. This type usually effects intensity values, but they may also be spatial, such as perspective distortions. The third type of variations are differences in the images that are of interest such as object movements, growths, or other scene changes. Variations of the second and third type are not directly removed by registration, but they make registration more difficult since an exact match is no longer possible. In particular, it is critical that variations of the third type are not removed. Knowledge about the characteristics of each type of variation effect the choice of feature space, similarity measure, search space, and search strategy which will make up the final technique. All registration techniques can be viewed as different combinations of these choices. This framework is useful for understanding the merits and relationships between the wide variety of existing techniques and for assisting in the selection of the most suitable technique for a specific problem.

A survey of image registration techniques

Let's read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd the perception of the visual world to read.

The Perception of the Visual World. By James J. Gibson. U.S.A.: Houghton Mifflin Company, 1950 (George Allen & Unwin, Ltd., London). Price 35s.

There are declines with age in speed of processing, working memory, inhibitory function, and long-term memory, as well as decreases in brain structure size and white matter integrity. In the face of these decreases, functional imaging studies have demonstrated, somewhat surprisingly, reliable increases in prefrontal activation. To account for these joint phenomena, we propose the scaffolding theory of aging and cognition (STAC). STAC provides an integrative view of the aging mind, suggesting that pervasive increased frontal activation with age is a marker of an adaptive brain that engages in compensatory scaffolding in response to the challenges posed by declining neural structures and function. Scaffolding is a normal process present across the lifespan that involves use and development of complementary, alternative neural circuits to achieve a particular cognitive goal. Scaffolding is protective of cognitive function in the aging brain, and available evidence suggests that the ability to use this mechanism is strengthened by cognitive engagement, exercise, and low levels of default network engagement.

/pdf/the-adaptive-brain-aging-and-neurocognitive-scaffolding-3igyn72710.pdf

The Adaptive Brain: Aging and Neurocognitive Scaffolding

A classic photographic task is the mapping of the potentially high dynamic range of real world luminances to the low dynamic range of the photographic print. This tone reproduction problem is also faced by computer graphics practitioners who map digital images to a low dynamic range print or screen. The work presented in this paper leverages the time-tested techniques of photographic practice to develop a new tone reproduction operator. In particular, we use and extend the techniques developed by Ansel Adams to deal with digital images. The resulting algorithm is simple and produces good results for a wide variety of images.

/pdf/photographic-tone-reproduction-for-digital-images-k89wmpv97f.pdf

Photographic tone reproduction for digital images

Blood vessels usually have poor local contrast, and the application of existing edge detection algorithms yield results which are not satisfactory. An operator for feature extraction based on the optical and spatial properties of objects to be recognized is introduced. The gray-level profile of the cross section of a blood vessel is approximated by a Gaussian-shaped curve. The concept of matched filter detection of signals is used to detect piecewise linear segments of blood vessels in these images. Twelve different templates that are used to search for vessel segments along all possible directions are constructed. Various issues related to the implementation of these matched filters are discussed. The results are compared to those obtained with other methods. >

/pdf/detection-of-blood-vessels-in-retinal-images-using-two-2lxvrugvz5.pdf

Detection of blood vessels in retinal images using two-dimensional matched filters

Reflected glare often interferes with vision. Since such glare is usually polarized it can be controlled with polarizers. The use of polarized filters to eliminate vertically polarized glare from blackboards and glossy printed material is presented. Practical means for the construction of such filters are discussed.

Control of vertically polarized glare.

Under many conditions below the Nyquist limit, a drifting grating briefly displayed on a CRT is consistently perceived as moving in the opposite direction. Taking into account the sample-and-hold operation of CRT’s, we have derived the temporal-frequency spectra of the displayed gratings and found that they have a broad range of components moving in either direction. We have measured the perceived direction of motion of over 150 different short-duration stimuli, and we have studied the relation that performance bears to narrow-band power imbalance—the normalized difference between power in the positive- and negative-frequency half-lines within a specific band. Perceived direction of motion is highly related to power imbalance in 1-Hz-wide bands centered between 10 and 15 Hz, but none of these bands alone can account for more than 84–91% of the variance of the data, and each band ostensibly fails to explain data from a subset of the stimuli. When broadband power imbalance is determined by weighting the spectrum with an inverted-U-shaped function peaking at ∼12 Hz, the explained variance increases to 91–97%. Our results suggest that the imputation of direction of motion to stimuli with complex spectra is based on broadband power imbalance determined after weighting the temporal-frequency spectrum with an inverted-U-shaped function.

Imputation of direction of motion in one dimension

Biofeedback auditif utilisee pour ameliorer une therapie d'insuffisance de convergence en complement aux methodes optometriques et orthoptiques. L'auteur presente une forme de reaction independante du systeme sensoriel visuel. Il emet l'hypothese que la biofeedback auditive obligerait et renforcerait la phase initiale du soin de la vision pour moderer une insuffisance de convergence de longue date avec profonde suppression. Le rapport qui concerne un sujet de 29 ans, n'ayant pas obtenu de resultats probants par les methodes classiques apres 4 semaines de traitement, et qui traite par bioreaction auditive a obtenu une amelioration apres 5 jours, tend a confirmer cette hypothese

Auditory biofeedback used to enhance convergence insufficiency therapy.

We describe the design of a driving simulator study to determine the effect of central visual field loss (due to macular disease) on pedestrian detection when driving. Pilot data suggest that a scotoma (blind area) in the central visual field can impair driving by increasing response time to hazardous circumstances.

https://ir.uiowa.edu/cgi/viewcontent.cgi?article=1338&context=drivingassessment

The Impact of Macular Disease on Pedestrian Detection: A Driving Simulator Evaluation

For the visual system, luminance contrast is a fundamental property of images, and is one of the main inputs of any simulation of visual processing. Many models intended to evaluate visual properties such as image discriminability compute perceived contrast by using contrast sensitivity functions derived from studies of human spatial vision. Such use is of questionable validity even for such applications (i.e. full-reference image quality metrics), but it is usually inappropriate for no-reference image quality measures. In this paper, we outline why the contrast sensitivity functions commonly used are not appropriate in such applications, and why weighting suprathreshold contrasts by any sensitivity function can be misleading. We propose that rather than weighting image contrasts (or contrast differences) by some assumed sensitivity function, it would be more useful for most purposes requiring estimates of perceived contrast or quality to develop an estimate of efficiency: how much of an image is making it past the relevant thresholds. 1. CONTRAST 1.1 Primacy For the visual system, luminance contrast is the fundamental carrier of information about images. Motion is perceived through temporal changes in luminance contrast; the most initial sensations of depth are formed from binocular combinations of monocularly sensed contrasts; chromatic variation is almost always correlated with luminance changes. All of these qualities (motion, depth, color) are important parts of normal visual experience, and thus of any full-quality representation of it; but a monochromatic, cyclopean still-image is a perfectly acceptable visual representation of a scene. Here we argue that in estimating the visual quality of an image, contrast thresholds are of principal importance; perceived (suprathreshold) contrast magnitudes although noticeable in side-by-side comparison are relatively less important; and that the specific sensitivity functions commonly used in standard practice to estimate perceived contrast and quality may be misapplied or inappropriate. 1.2 Measurement Given the primary importance to vision of luminance contrast, it is of great practical and theoretical importance to have operational measures of it (1). The simplest summary measures will usually fail in characterizing the apparent contrast of an image, and thus are not used except for the simplest of patterns. Michelson contrast, the absolute range of luminances in a pattern, is thus not widely used except for periodic grating patterns - it errs by ignoring too much of an image's spatial variation. A much more common measure of a complex image's contrast is the standard deviation of luminances in an image (RMS contrast), a measure of the average deviation in luminance from the image mean over a specified spatial area. This measure is less susceptible to extreme values in an image, and thus tracks better with perceptual appearance of image contrast. Still, RMS contrast is a relatively poor predictor of perceived contrast - it errs by equally weighting all of the image's spatial variation and has been shown repeatedly to fail in predicting perceived image quality. 1.3 Perception The visual system responds to images through a system of overlapping neural networks, repeated across the visual field, which are sensitive to different spatial scales, and perceived contrast is related to the response of these networks. The

Eli Peli

Papers

Control of vertically polarized glare.

Imputation of direction of motion in one dimension

Auditory biofeedback used to enhance convergence insufficiency therapy.

The Impact of Macular Disease on Pedestrian Detection: A Driving Simulator Evaluation

Complexities of Complex Contrast