Abstract: Disclosed is an input image data compressor which comprises an image recording controller for generating image information on respective input objects from the input image data, generating image information on a moving object using the image information, comparing the previously input image data with the presently input image data, generating new image information on the moving object and compressing the new image information; a storage unit for storing signals or data generated during compression operation of the image recording controller in a corresponding established address; and a compressed image storage unit for storing the compressed image data compressed by the control operation of the image recording controller.

Abstract: In a method for fractal coding of signals, in which a domain block d is investigated for a range block r to be transmitted from an original signal, so that, after using the calculation rule r*=v·d+b, an approximated range block r* is generated, v·d being a linear function and b being an offset vector, the offset vector b in general has different components b=(b1, b2, . . . , bn) the offset vector b preferably being composed of weighted orthogonal basic functions of an orthogonal transformation.

Abstract: The method for primary processing according to the invention takes into account a minimum dimension and a partition of a set of data into so-called “initial elementary” subsets (Ki). It includes: a) for each elementary subset which size is larger than the minimum dimension, one iteration of: a division suitability estimation step, and when appropriate, a step of “supplementary partitioning” of the said subset, b) a “construction” step of a global multidimensional mapping and non-linear mapping, the restrictions of the global mapping to the elementary subsets (Ki) being composed of elementary mappings, the fixed point of the global mapping constituting an approximation of all or part of this set, the set of parameters (ai, b) determined by the restrictions constituting an approximation of the said set of data.

Abstract: A block including a subject pixel is formed from an original image. A first class information generation circuit calculates similarity between a decimated block that is obtained by decimating pixels constituting the block and a reduced block obtained by reducing the block (self-similarity of an image). On the other hand, a second class information generation circuit detects a pattern of pixel values of pixels that are arranged in a direction with highest self-similarity in the reduced block (or the decimated block). A final class determination circuit determines a class of the block including the subject pixel based on outputs of both of the first class information generation circuit and the second class information generation circuit. A process corresponding to the thus-determined class is executed.

Abstract: A method of producing a transform decomposition of data having an odd length the method comprising the steps of dividing the data into a portion having an even length of one element; performing a discrete wavelet transform on the even length data to produce low frequency subband data and high frequency subband data; adding the difference of the one element and an adjacent element to high frequency subband data. Preferably the transform is a Discrete Wavelet Transform utilised in the compression of image data.

Abstract: The present invention relates to the automatic search for an image sample (f′) in images (f) of a data base. The sample and the images are compressed using their fractal properties, in the form of relations linking their ranges (R) to area or domains (D) of the same image. According to the invention, the comparison relates to indexes registering the geometrical characteristics of these relations. Various means are proposed for permitting a profitable search and in particular a limitation of the distance between ranges and domains of the image (f).

Abstract: A technique for encoding an interlaced picture comprises the steps of rearraying the interlaced picture on a scanning line basis, splitting the re-arrayed picture into a plurality of first block portions and splitting the re-arrayed picture into a plurality of second block portions. Each second block portion is transform processed to generate a plurality of transformed block portions, and it is determined which transformed block portion is most similar to a preselected first block portion. The second block portion corresponding to the determined transformed block portion is selected, and block position information indicating the position of the selected second block portion and a transformation parameter representing the transform processing of the selected second block portion are output.

Abstract: In a method of data reduction of a luminance and/or chrominance signal of a digital picture signal by means of fractal image coding, in which method each image of the luminance/chrominance signal is divided into range blocks of n.times.n pixels each, in which a domain block is searched for each range block, which domain block is imageable on the range block with a minimal deviation while using a transformation function, which domain blocks have a larger size than the range blocks, and in which information on the transformation functions is transmitted, from which information the image data are regained at the receiver end in an iterative process, the search is facilitated in that a digital search tree strategy is employed in the search for that domain block which is imageable on a range block with a minimal deviation while using a transformation function.

Abstract: A block including a subject pixel is formed from an original image. A first class information generation circuit calculates similarity between a decimated block that is obtained by decimating pixels constituting the block and a reduced block obtained by reducing the block (self-similarity of an image). On the other hand, a second class information generation circuit detects a pattern of pixel values of pixels that are arranged in a direction with highest self-similarity in the reduced block (or the decimated block). A final class determination circuit determines a class of the block including the subject pixel based on outputs of both of the first class information generation circuit and the second class information generation circuit. A process corresponding to the thus-determined class is executed.

Abstract: A method is provided for the fractal representation of data in which a representative continuous n-dimensional surface is defined as a first approximation to the original data. Residual data is formed from the date and the n-dimensional surface, and is then divided into a first number of regions. For each of the first number of regions, the following steps are performed: A number of domain regions are determined from the data; for a current one of each of the domain regions, a second representative n-dimensional surface is formed from the current domain; a (domain residual is formed from the current domain region; and the second representative n-dimensional surface, and a closest distance or error measure is determined. After processing each of the regions, the representation of data is stored.

Abstract: Color digital image data is encoded and compressed by a technique which combines the advantages of both wavelet and fractal encoding. The technique produces an encoded image separated by color components which can be efficiently matched to other compressed images in order to identify the image being processed. The encoding technique divides the images at numerous scales produced by wavelet transformations and forms blocks comprising of groups of pixels at each scales. The average modulus values and average angles values of the data in each of the blocks are compared to the next higher scale. Each scale is then encoded for the blocks which have corresponding matching blocks in the adjacent scale. The technique provides the edge retention benefits of wavelet and the compression benefits of fractal encoding and also accelerates the matching process between the scales. A decoding technique which uses a cross scale approximation of wavelet coefficients is used to reconstruct the image.

Abstract: In a method of data reduction of a luminance and/or chrominance signal of a digital picture signal by means of fractal image coding, in which method each image of the luminance/chrominance signal is divided into range blocks of n.times.

Abstract: A method is proposed for checking convergence in fractal image coding. In this case, a digitized image is divided into a number of range blocks (R.sub.i, R.sub.i+1) and into a number of domain blocks (D.sub.j, D.sub.k). A similar domain block is determined in relation to each range block. If necessary, in this process a transformation of a domain block is undertaken in order to map the domain block onto a range block. The assignment of the domain block to the range block including the transformation parameters represents the fractal code for the image. A reduced transformation matrix is set up to check convergence of the fractal code. The largest absolute eigenvalue of the transformation matrix is determined approximately. The entire method can be carried out in this case hierarchically. In a first approximation step, at least the row sum norm of each row of the reduced transformation matrix is checked. In further steps, further rows are combined to form square matrices of higher dimension.

Abstract: Fractal image coding of single images or image sequences is described, which yields an improvement of the encoding result as well as a reduction of computations, whereineach image is divided into range blocks which do not overlap and jointly comprise the complete image contents,range regions are generated, each comprising a range block which is smaller than the range region concerned, and the rest of the range region is filled up with a predetermined signal value,domain regions are generated having the same size as the range regions and comprise parts of the image contents, preferably also in a transformed form,the image data of the range regions and the domain regions are subjected to a Fourier transform,a conjugate-complex signal is formed from one of the two transformed signals and multiplied by the other signal,this product is normalized at a predetermined amplitude,the normalized signal is subjected to an inverse Fourier transform,for each range region, the maximum value of this retransformed signal is d

Abstract: A method is provided for the fractal representation of data in which the data (902) is divided into a first series of overlapping regions. A weighting function is applied to the regions. The weighted regions are expanded onto an orthonormal basis, and the orthonormal expansion is truncated at a predetermined point. A residue is formed between the data (902) and the truncated orthonormal expansion, and a fractal approximation to the residue is determined.

Abstract: The present invention is directed to providing a method and apparatus for enhanced processing of partitioned image data in a manner which permits efficient processing (for example, real-time processing) of the image data without sacrificing the quality of the reconstructed image. In accordance with exemplary embodiments, image data associated with a partitioned frame of input image data is stored along with information which identifies relative placement of each partitioned subimage within the frame of image data. The information is retained during processing of the input frame of image data, such that the original image can be reconstructed therefrom without the inclusion of holes or artifacts due to misalignment of boundaries. Thus, an input frame of image data which has been partitioned can be efficient transmitted, stored and rendered without concern that quality of the reconstructed image will be sacrificed.

Abstract: For fractal image coding optimal scaling factors for the image contents in the domain blocks are searched. Each image is divided into analysis blocks, which jointly represent the whole image. The analysis blocks are embedded in analysis regions, which contain besides the analysis blocks areas with a predetermined signal value. Also, comparison regions are formed, which contain at least parts of the image and which have the same size as the analysis regions. The analysis regions and the comparison regions are Fourier transformed. The transformed signals are converted logarithmically. The logarithmized signals are again Fourier-transformed. One of these signals is converted in its conjugate-complex form before both signals are multiplied. The product is normalized, so that it no longer contains amplitude information. Then the signal is subjected to an inverse Fourier-Transformation. If the signal has been logarithmized then it is de-logarithmized.

Abstract: Digital image data is encoded and compressed by a technique which combines the advantages of both wavelet and fractal encoding. The technique produces an encoded image which can be efficiently matched to other compressed images in order to identify the image being processed. The encoding technique spatially decimates the images at numerous frequency scales produced by wavelet transformations and forms blocks comprising of groups of pixels at each frequency scales. The average modulus values and average angle values of the data in each of the blocks are compared to the next higher scale. Each frequency scale is then encoded for the blocks which have corresponding matching blocks in the adjacent scale. The technique provides the edge retention benefits of wavelet and the compression benefits fractal encoding and also accelerates the matching process between the scales. A decoding technique which includes a synthetic edge procedure is used to reconstruct the image.

Abstract: A method for transmitting fractal transform parameters generated by a variety of compressors using different fractal transform parameters is disclosed. The method includes generating an universal header having image reference data, color space data, fractal transform region reference data, and file decoding data and generating a fractal transform data segment having fractal transform parameters for domains and ranges used by a compressor to generate fractal transform parameters. The image reference data includes image dimensions expressed in physical size units so that the regeneration of the image at a decompressor is resolution independent. The color space parameters include identification of the original image color space and may include identification of a color space into which the original image is converted.

Abstract: An image compression device comprises an image smoothing device which produces a smooth image by performing a smoothing process on an original image, an edge detection device which produces an edge image by subtracting said smoothed image from said original image, a fractal encoding device which encodes said smoothed image by fractal image compression, a reversible encoding device which encodes said edge image by reversible image compression, and an output device which combines the output of said fractal encoding means and the output of said reversible encoding means, and outputs said data as compressed data of the original image.

Abstract: The fractal image compression device of the present invention contemplates a control unit for dividing a composite image into a plurality of range blocks and a plurality of domain blocks, classifying the range blocks and domain blocks into several classes according to their respective attributes, and controlling an overall operation of the device. A page memory stores image data received from an external source, and provides output of the image data via control of the control unit. A domain block memory receives first pixel data within the domain blocks from the page memory, and stores the first pixel data via control of the control unit. A range block memory receives second pixel data within the range blocks from the page memory, and stores the second pixel data via control of the control unit.

Abstract: A method of encoding a digital image using adaptive partitioning in an iterated transformation image compression system is provided. A set of ranges R is initialized to include at least two uncovered ranges. A set of domains D is initialized to include only one member which is the entire image area.For each uncovered range in the set R: A transformation is generated for each domain in the set of domains. Each domain is transformed into corresponding transformed images to map onto each uncovered range in the set R. Each domain's transformation is optimized and is indicative of a domain's corresponding optimized transformation image for an associated uncovered range. Each optimized transformation image is compared with the associated uncovered range to provide error data as a function of the difference therebetween. The associated uncovered range is redefined as a covered range when the error data for the associated uncovered range is within predefined limits.

Abstract: To achieve an enhanced data reduction, a method of fractal image coding, in which method an image to be encoded is divided into range blocks which do not overlap and jointly cover the image contents completely, in which domain blocks comprising areas of the image contents in their original form or in a transformed form are generated from the image contents, and all areas of the image contents are covered by at least one domain block, for each range block the domain block most similar to the range block being searched, and the addresses of the domain blocks found as the most similar and possibly the transform functions used for their generation being transmitted instead of the data of the range blocks, is characterized in that, in a sequence of images, the fractal image coding performed exclusively within the images is only performed with basic images comprised in the image sequence at selectable time intervals, in that, for intermediate images provided between the basic images, the same range and domain block

Abstract: A method and system for classification of biological materials is described. The system (100) includes a microscope (10), a digitizing camera (20) and a computer (30). The method includes the steps of capturing the digital image (40) of the biological material or cell (12) using the digitizing camera preferably through the microscope (10). The captured image is digitized and displayed on the computer screen (32). The digitized image is then enhanced using a grey level value thresholding process, a cluster recognition process and a boundary determination process. The resulting enhanced image (40C) is then used to determine the perimeter surface (40D) of the cell. The enhanced image is subjected to a box counting routine in which the number of boxes occupied by the perimeter surface is calculated for various different box sizes. The box counting calculations are plotted using a power-law analysis.

Abstract: A system and method are disclosed for representing a data set by selecting a data transformation function and a data masking function. Preferably, the data set transformation and data masking functions are used to generate an attractor that more accurately represents the data set than an attractor generated by the data transformation function alone. The data masking function is a set of exclusionary data elements which are used to terminate data transformations for data elements which generate the attractor. Preferably, the data masking function is defined as a polygon for a two dimensional space. When the data masking function is incorporated with the data transformation function, the attractor normally produced by the data set transformation function is constrained to more accurately represent the data set.

Abstract: Image compression is accomplished by dividing an image into blocks which are encoded and compressed by finding similarities among the blocks. Image quality and speed are increased through several mechanisms such as varying the size of the blocks when image edges or test is present, by comparing the image blocks to prestored image patterns rather than other portions of the image, using raw data rather than compressed data under certain conditions and the use of inspection areas to increase the possibility of finding the most similar area quickly.

Abstract: A method for encoding and decoding digital signals, particularly speech signals, by separating the original signal into a linear and nonlinear portions, the nonlinear portion may have linear aspects. The linear portion is encoded by LPC techniques and the nonlinear portion is encoded by use of a fractal transform. The encoded signal consists of LPC filter coefficients and fractal transform coefficients. The encoded signal is decoded by separating the LPC coefficients and fractal coefficients, using the LPC coefficients to generate an LPC filter, decoding the fractal coefficients using a fractal transform decoding method to obtain an error signal, and exciting the LPC filter with the decoded error signal to obtain decoded digital signals.

Abstract: A method of extracting a contour of a contrasted area in a digitized image made up of pixels having different intensity levels defining the contrasted area is based on minimizing the energy of an initial active contour to which are applied stresses derived from a potential image obtained by processing the image. The potential image is obtained from a multifractal analysis of the image so that each element of the potential image is representative of a local fractal dimension in the locality of a corresponding pixel in the image. This improves the behavior of the active contour when it is deformed by the stresses.

Abstract: A method of identifying and classifying pre-detected target candidates in an image using pixel intensity and a fractalization process applied to the image. A raw analog image is digitized and normalized. The normalized pixel intensity content of the image is converted to fractal dimensions using a small and a large fractal box, sequentially. An array of special fractal features satisfying predetermined classification thresholds is prepared from the fractal dimensions for each box centered about each pre-detected target candidate in the image, thus classifying the detected objects as targets.

Abstract: A method of fractal coding of data and apparatus therefor, which method comprises dividing data into domains, determining a set of transformations relating the domains to the data in such a manner as to minimize error between the data and an approximation to the data obtained by application of the transformation, and providing an expression of a series of quantized fractal coefficients characterizing the transformations. A transformation includes at least one part indicating a domain and at least another (functional) part indicating a value for a measure associatable with a specific domain or aspect thereof.

Abstract: A method and apparatus are described for-encoding a three-dimensional array of data representing a physical entity, such as an image (or sequence of frames), by means of its local symmetries. This encoding yields both compression and a resolution-independent description which allows reconstruction of the image to an arbitrary scale. Spatial zooming and interframe interpolation can be achieved without significant loss of information.

Abstract: A system for generating deciphering symbols or roots and particularly to systems employing fractal metric characterizations, which in turn are based upon fractal dimensions of less than the whole of the data to be characterized.

Abstract: An encoder and decoder system for compressing discrete data sequences is disclosed. The encoder includes a self-affine map generator and a backward adaptive map generator which model source vectors formed from a discrete data sequence. The self-affine map generator uses known modeling techniques to determine map parameters for mapping functions. The mapping functions are evaluated by computing a collage error and the mapping function corresponding to the smallest collage error is selected. The backward adaptive map generator determines map parameters for mapping functions which map vectors previously generated to represent the discrete data sequence to the source vector. A distance measurement is computed for each target vector/mapping function combination and the mapping function corresponding to the smallest distance measurement is selected.

Abstract: A system and method for analyzing a set of data elements is disclosed. The method includes the steps of transforming data elements of a transform data space using the states of data elements comprising a data set and determining whether the transformed data elements have structure in the transform data space. The transformation of the data elements is performed by iteratively selecting mapping transformations corresponding to the states of successive data elements in the data set and applying the mapping transformations to successive transformations in the transform data space. By viewing the transformations in the transform data space, structure may be ascertained and evaluated to obtain information about the data set. The inventive system includes a transformer that changes state in response to the state of the next data element received from the data set and transforms the last transformation stored in the transform data space.

Abstract: A method for compressing data for storage or transmission. Given a complex polynomial and a value assigned to each root, a root generated data file (RGDF) is created, one entry at a time. Each entry is mapped to a point in a complex plane. An iterative root finding technique is used to map the coordinates of the point to the coordinates of one of the roots of the polynomial. The value associated with that root is assigned to the entry. An equational data compression (EDC) method reverses this procedure. Given a target data file, the EDC method uses a search algorithm to calculate a set of m complex numbers and a value map that will generate the target data file. The error between a simple target data file and generated data file is typically less than 10%. Data files can be transmitted or stored without loss by transmitting the m complex numbers, their associated values, and an error file whose size is at most one-tenth of the size of the input data file.

Abstract: A fractal image compression method performed in a digital image processing device includes the steps of: dividing image data representative of a composite image into a plurality of range blocks each having a first predetermined size; designating, for each of the range blocks, a plurality of domain blocks each having a second predetermined size, wherein each one of the plurality of domain blocks has a subportion that includes an entire portion of the corresponding range block; calculating coefficients of a contractive transformation function to match a plurality of spacially transformed domain blocks to each range block; calculating distortion errors between the range blocks and their corresponding pluralities of spacially transformed domain blocks; comparing the distortion errors among the spacially transformed domain blocks for each corresponding range block, and selecting a spacially transformed domain block having a minimum distortion error as a maximum similarity block for each corresponding range block;

Abstract: A digital signal encoding method including the steps of defining first and second components of an original digital signal on each of two scales, fractal-processing the two first components by conducting a comparison therebetween and generating an encoded digital signal including a representation of at least one of the smooth components and a representation of the result of the fractal-processing step.