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A general method is proposed for the synthesis of texture. It is based on a model which treats the pixels (picture elements) of a digitized textural scene as a two-way seasonal time series. This method possesses the desirable characteristic that the parameters needed for synthesis are derived directly from the analysis of the “parent” texture (texture to be imitated). With the help of well-developed methods in the time series analysis the process that generates the pixels of the parent texture is identified. From a set of boundary conditions the future values of the time series are generated which in essence are the pixels of the synthesised texture. The effectiveness of this method is illustrated with examples.

An extension to the basic concept of correlation detection as a means of image registration is developed. The technique involves linear spatial preprocessing of the inages to be registered prior to the application of a correlation measure. This preprocessing operation utilizes the spatial correlation within each image and greatly improves the detectability of image misregistration. An analysis of the computational aspects of the algorithm is given. Also, results of a computer simulation to evaluate the technique are given.

Further work is described on simple sets of parallel operations that detect "texture edges" (abrupt discontinuities in the average values of local picture properties), as well as spots or streaks that are texturally different from their surrounds.

An area which has rapidly gained interest in the last few years is that of remote sensing by imagery.1, 2 Certainly the successful mission of the ERTS has contributed to an expanding interest and increased potential.3 The potential uses of such remotely sensed data cover a variety of applications, including land use studies, crop quality, accurate map making, and evaluating natural resources. In utilizing this data in a particular application, a significant problem is the amount of data that must be processed to obtain specific information or features pertinent to the application. This is inherent in image or visual information; when this is multiplied by a large number of the available images, the problem of obtaining details or small features from such images is significant. This is particularly true when some set of features is to be used in a parametric pattern recognition scheme. However, there are many instances when one is interested in identifying an area or region which may encompass many details, but is small compared with an overall image and represents a defined entity. Then, if one is interested in identifying or classifying such a region, its gross characteristics must be represented while ignoring small details that may vary significantly from one sample observation to another.

Computer methods are presented which deal with the problems of visual texture, specifically Texture Analysis and Texture Synthesis. The Decision Theory Method, as its name indicates, is based on the principles of statistical decision theory. This method in conjunction with the Internal Covering Theory, automatically generates a set of interval complexes which act as 2-D filters that detect texture features in the scene of analysis. The versatility of this method to deal with various problems of visual texture, such as scene segmentation using textural information, extraction of texture borders, discrimination/recognition of both spatially and chromatically textured scenes, etc. is demonstrated. A model is proposed that views the pixels of a digitized textural scene as a two- way seasonal time series. Based on this model, a method is developed for synthesis of natural looking textures. This method possesses a desirable quality that the parameters needed for the synthesis are derived from the analysis of parent'' texture, i.e., the texture to be imitated. Extending the concepts of two-dimensional formal grammars, known as array grammars, multilevel array grammars'' are introduced. These are shown capable of generating complex texture scenes, specifically brickwall-type'' texture, that is, those textures which are perceived at many levels andmore » at each level, they can be either structural or statistical. A way of specifying these grammars for texture scenes in real cases, with the help of interval complexes,'' is also indicated. (96 references) (auth)« less

Operational Calculus based on the Two-Sided Laplace Integral By Dr. Balth van der Pol and Dr. H. Bremmer. Second Edition. Pp. xiii + 415. (Cambridge: At the University Press, 1955.) 60s. net.

The evaluation of an image must depend upon the purpose for which the image was obtained and the manner in which the image is to be examined. Where the goal is extraction of information and where the image is to be processed prior to viewing, the information content of the image is the only true evaluation criterion. Under these conditions, the improvement achieved by processing can be evaluated by comparing the ability of the human observer to extract information from the image before and after processing. The extent to which the processing approaches the optimum can be evaluated by determining the fraction of the total information content of the image which can be visually extracted after processing. The basic mathematical concepts of image processing are indicated, relating the input point spread function (p. s. f. of the unprocessed image), the processing point spread function (p. s. f. which defines the processing operation), and the output point spread function (p. s. f. of the processed image), and their Fourier domain equivalents. Examples are shown of images which have been processed and the details of the processing operations are described.

The advent of increased government involvement in occupational health maintenance with compensation for affected individuals is requiring new approaches to medical decision making. One aspect of this involvement will perhaps include the automatic mass diagnostic screening of medical films for the detection of a specffic abnormality with an occupational etiology. The results of two complementary approaches for performing diagnostic screening for presence and profusion of coal worker's pneumoconiosis from the routine posterior-anterior chest radiograph are presented. The first is a digital approach utilizing the measurement of image texture, while the second uses hybrid optical-digital methods involving the optical Fourier tramsform. Both approaches yielded classification results comparable to experienced radiologists.