Method for a detailed measurement of image intensity nonuniformity in magnetic resonance imaging

In magnetic resonance imaging (MRI), the MR signal intensity can vary spatially and this spatial variation is usually referred to as MR intensity nonuniformity. Although the main source of intensity nonuniformity arises from B, inhomogeneity of the coil acting as a receiver and/or transmitter, geometric distortion also alters the MR signal intensity. It is useful on some occasions to have these two different sources be separately measured and analyzed. In this paper, we present a practical method for a detailed measurement of the MR intensity nonuniformity. This method is based on the same three-dimensional geometric phantom that was recently developed for a complete measurement of the geometric distortion in MR systems. In this paper, the contribution to the intensity nonuniformity from the geometric distortion can be estimated and thus, it provides a mechanism for estimation of the intensity nonuniformity that reflects solely the spatial characteristics arising from B-1. Additionally, a comprehensive scheme for characterization of the intensity nonuniformity based on the new measurement method is proposed. To demonstrate the method, the intensity nonuniformity in a 1.5 T Sonata MR system was measured and is used to illustrate the main features of the method. (c) 2005 American Association of Physicists in Medicine.

Systematic changes in the duration and precision of interception in response to variation of amplitude and effector size

The results of two experiments are reported that examined how performance in a simple interceptive action (hitting a moving target) was influenced by the speed of the target, the size of the intercepting effector and the distance moved to make the interception. In Experiment 1, target speed and the width of the intercepting manipulandum (bat) were varied. The hypothesis that people make briefer movements, when the temporal accuracy and precision demands of the task are high, predicts that bat width and target speed will divisively interact in their effect on movement time (MT) and that shorter MTs will be associated with a smaller temporal variable error (VE). An alternative hypothesis that people initiate movement when the rate of expansion (ROE) of the target's image reaches a specific, fixed criterion value predicts that bat width will have no effect on MT. The results supported the first hypothesis: a statistically reliable interaction of the predicted form was obtained and the temporal VE was smaller for briefer movements. In Experiment 2, distance to move and target speed were varied. MT increased in direct proportion to distance and there was a divisive interaction between distance and speed; as in Experiment 1, temporal VE was smaller for briefer movements. The pattern of results could not be explained by the strategy of initiating movement at a fixed value of the ROE or at a fixed value of any other perceptual variable potentially available for initiating movement. It is argued that the results support pre-programming of MT with movement initiated when the target's time to arrival at the interception location reaches a criterion value that is matched to the pre-programmed MT. The data supported completely open-loop control when MT was less than between 200 and 240 ms with corrective sub-movements increasingly frequent for movements of longer duration.

Using the Amazon metric to construct an image database based on what people do, not what they say

Current image database metadata schemas require users to adopt a specific text-based vocabulary. Text-based metadata is good for searching but not for browsing. Existing image-based search facilities, on the other hand, are highly specialised and so suffer similar problems. Wexelblat's semantic dimensional spatial visualisation schemas go some way towards addressing this problem by making both searching and browsing more accessible to the user in a single interface. But the question of how and what initial metadata to enter a database remains. Different people see different things in an image and will organise a collection in equally diverse ways. However, we can find some similarity across groups of users regardless of their reasoning. For example, a search on Amazon.com returns other products also, based on an averaging of how users navigate the database. In this paper, we report on applying this concept to a set of images for which we have visualised them using traditional methods and the Amazon.com method. We report on the findings of this comparative investigation in a case study setting involving a group of randomly selected participants. We conclude with the recommendation that in combination, the traditional and averaging methods would provide an enhancement to current database visualisation, searching, and browsing facilities.

A spatial statistic to determine appropriate field sampling size for linking image and field data

Proceedings of the 11th Australasian Remote Sensing and Photogrammetry Conference

Semi-global techniques in image matching and change detection with applications to civil and environmental engineering.

This work of thesis wants to present a dissertation of the wide range of modern dense matching algorithms, which are spreading in different application and research fields, with a particular attention to the innovative “Semi-Global” matching techniques. The choice of develop a semi-global numerical code was justified by the need of getting insight on the variables and strategies that affect the algorithm performances with the primary objective of maximizing the method accuracy and efficiency, and the results level of completeness. The dissertation will consist in the metrological characterization of the proprietary implementation of the semi-global matching algorithm, evaluating the influence of several matching variables and functions implemented in the process and comparing the accuracy and completeness of different results (digital surface models, disparity maps and 2D displacement fields) obtained using our code and other commercial and open-source matching programs in a wide variety of application fields.

Neural adjustments to image blur

Blur is an intrinsic feature of retina images that varies widely across images and observers, yet the world still typically appears 'in focus'. Here we examine the putative role of neural adaptation1 in the human perception of image focus by measuring how blur judgments depended on the state of adaptation. Exposure to unfocused images has previously been shown to influence acuity and contrast sensitivity and here we show that adaptation can also profoundly affect the actual perception of image focus.

Applications of fractals to image data compression

Digital image processing is exploited in many diverse applications but the size of digital images places excessive demands on current storage and transmission technology. Image data compression is required to permit further use of digital image processing. Conventional image compression techniques based on statistical analysis have reached a saturation level so it is necessary to explore more radical methods. This thesis is concerned with novel methods, based on the use of fractals, for achieving significant compression of image data within reasonable processing time without introducing excessive distortion. Images are modelled as fractal data and this model is exploited directly by compression schemes. The validity of this is demonstrated by showing that the fractal complexity measure of fractal dimension is an excellent predictor of image compressibility. A method of fractal waveform coding is developed which has low computational demands and performs better than conventional waveform coding methods such as PCM and DPCM. Fractal techniques based on the use of space-filling curves are developed as a mechanism for hierarchical application of conventional techniques. Two particular applications are highlighted: the re-ordering of data during image scanning and the mapping of multi-dimensional data to one dimension. It is shown that there are many possible space-filling curves which may be used to scan images and that selection of an optimum curve leads to significantly improved data compression. The multi-dimensional mapping property of space-filling curves is used to speed up substantially the lookup process in vector quantisation. Iterated function systems are compared with vector quantisers and the computational complexity or iterated function system encoding is also reduced by using the efficient matching algcnithms identified for vector quantisers.

Application of digital image processing techniques to the photometric testing of vehicle headlamps

The aim of this Interdisciplinary Higher Degrees project was the development of a high-speed method of photometrically testing vehicle headlamps, based on the use of image processing techniques, for Lucas Electrical Limited. Photometric testing involves measuring the illuminance produced by a lamp at certain points in its beam distribution. Headlamp performance is best represented by an iso-lux diagram, showing illuminance contours, produced from a two-dimensional array of data. Conventionally, the tens of thousands of measurements required are made using a single stationary photodetector and a two-dimensional mechanical scanning system which enables a lamp's horizontal and vertical orientation relative to the photodetector to be changed. Even using motorised scanning and computerised data-logging, the data acquisition time for a typical iso-lux test is about twenty minutes. A detailed study was made of the concept of using a video camera and a digital image processing system to scan and measure a lamp's beam without the need for the time-consuming mechanical movement. Although the concept was shown to be theoretically feasible, and a prototype system designed, it could not be implemented because of the technical limitations of commercially-available equipment. An alternative high-speed approach was developed, however, and a second prototype syqtem designed. The proposed arrangement again uses an image processing system, but in conjunction with a one-dimensional array of photodetectors and a one-dimensional mechanical scanning system in place of a video camera. This system can be implemented using commercially-available equipment and, although not entirely eliminating the need for mechanical movement, greatly reduces the amount required, resulting in a predicted data acquisiton time of about twenty seconds for a typical iso-lux test. As a consequence of the work undertaken, the company initiated an 80,000 programme to implement the system proposed by the author.

Sparsity and "something else": an approach to encrypted image folding

A property of sparse representations in relation to their capacity for information storage is discussed. It is shown that this feature can be used for an application that we term Encrypted Image Folding. The proposed procedure is realizable through any suitable transformation. In particular, in this paper we illustrate the approach by recourse to the Discrete Cosine Transform and a combination of redundant Cosine and Dirac dictionaries. The main advantage of the proposed technique is that both storage and encryption can be achieved simultaneously using simple processing steps.

Applying Information Foraging Theory to understand user interaction with content-based image retrieval

The paper proposes an ISE (Information goal, Search strategy, Evaluation threshold) user classification model based on Information Foraging Theory for understanding user interaction with content-based image retrieval (CBIR). The proposed model is verified by a multiple linear regression analysis based on 50 users' interaction features collected from a task-based user study of interactive CBIR systems. To our best knowledge, this is the first principled user classification model in CBIR verified by a formal and systematic qualitative analysis of extensive user interaction data. Copyright 2010 ACM.