Abstract: A distribution evaluation apparatus includes an evaluation value calculating unit that calculates weighted energy, as an evaluation value representing distribution of located objects x and y, by calculating a product resulting from multiplying weighting function values ?(x) and ?(y) and probability density function values ?(x) and ?(y) representing densities or sizes of the located objects x and y, by a mutual influence value determined by a function fr having as a variable a distance between the located objects x and y, and then by summing the resulting products with respect to all the located objects x and y into the weighted energy, and an evaluating unit that evaluates the distribution of the located objects in accordance with the evaluation value calculated by the evaluation value calculating unit.

Abstract: An image processing mask creating method includes calculating cluster energy of each point in an image processing mask, ranking the points in ascending order or descending order on the basis of the calculated cluster energy values, and allocating threshold values to the points in the image processing mask on the basis of the ranks as the process result of the ranking, wherein the cluster energy is defined as the sum of interaction values fr(?x?y?) having the distance ?x?y? between a target point x and a point y belonging to a cluster not including the target point x as a parameter.

Abstract: An image processing apparatus to perform an enlarging process for an original image constituted by C colors (C?2) includes a target color selecting unit that selects two target colors C1 and C2 for each local region of the original image, a sorting unit that sorts the local region on the basis of a layout of the target colors selected by the target color selecting unit, and a processing unit that determines pixel values after enlargement from the target colors C1 and C2 in accordance with a result of the sorting performed by the sorting unit.

Abstract: An image processing mask creating method includes calculating cluster energy of each point in an image processing mask, ranking the points in ascending order or descending order on the basis of the calculated cluster energy values, and allocating threshold values to the points in the image processing mask on the basis of the ranks as the process result of the ranking, wherein the cluster energy is defined as the sum of interaction values fr(?x?y?) having the distance ?x?y? between a target point x and a point y belonging to a cluster not including the target point x as a parameter.

Abstract: A distribution evaluation apparatus includes an evaluation value calculating unit that calculates weighted energy, as an evaluation value representing distribution of located objects x and y, by calculating a product resulting from multiplying weighting function values ?(x) and ?(y) and probability density function values ?(x) and ?(y) representing densities or sizes of the located objects x and y, by a mutual influence value determined by a function fr having as a variable a distance between the located objects x and y, and then by summing the resulting products with respect to all the located objects x and y into the weighted energy, and an evaluating unit that evaluates the distribution of the located objects in accordance with the evaluation value calculated by the evaluation value calculating unit.

Abstract: An image processing apparatus includes: a table generation unit that generates a table in which a coefficient set including predetermined weighting coefficients and pixels contained in a resolution converted image are related to each other on the basis of a size of an input image and a size of a resolution converted image; a coefficient selecting unit that selects a coefficient set to be applied for a calculation of a pixel value in the resolution converted image out of plural coefficient sets on the basis of a table generated by the table generation unit; and a pixel value calculating unit that calculates pixel values to be used in the resolution converted image resulting from the resolution conversion of the input image on the basis of the coefficient set selected by the coefficient selecting unit and plural pixel values contained in the input image.

Abstract: An image processing apparatus includes an information acquiring portion that acquires information on image process conditions for processing image data, a creating portion that creates additional image data, serving as a watermark image, with additional information to be embedded into the image data on the basis of the information on the image process conditions acquired, and a merging portion that merges the image data with the additional image data to create composite image data.

Abstract: An image processing apparatus generates a sub-self-similar set F, which is a subset of a self-similar set A with respect to contraction maps f1, . . . , fn and forms an image expressing the sub-self-similar set F. The apparatus includes a base-address-set designating section, a generation-rule acquiring section and a sub-self-similar set generating section. The base-address-set designating section selects m addresses each of which formed of infinite sequence of {1, . . . , n} and generates a base address set M including the selected addresses. The generation-rule acquiring section acquires a rule of generating a hypothetical sub-self-similar set G, which is a subset of a hypothetical self-similar set B with respect to n hypothetical contraction maps g1, . . . , gn, by using the generated base address set M. The sub-self-similar set generating section generates a sub-self-similar set F, which is a subset of the self-similar set A.

Abstract: A domain block image is extracted from an original image by a domain block extracting section, and the domain block image is classified by a domain block classifying section. A range block extracting section extracts a range block image larger than the domain block image from the original image, and a reduced range block forming section reduces the range block image at the same size as the domain block image. A similarity degree judging section judges a similarity degree between the reduced range block image and the domain block image, and an improved domain block forming section performs a conversion of pixel values with respect to the reduced range block image in accordance with this similarity degree. Further, an edge enhancement processing section executes an edge enhancement processing as to the step edge portion so as to obtain an improved domain block image.

Abstract: An image processing apparatus includes: a table generation unit that generates a table in which a coefficient set including predetermined weighting coefficients and pixels contained in a resolution converted image are related to each other on the basis of a size of an input image and a size of a resolution converted image; a coefficient selecting unit that selects a coefficient set to be applied for a calculation of a pixel value in the resolution converted image out of plural coefficient sets on the basis of a table generated by the table generation unit; and a pixel value calculating unit that calculates pixel values to be used in the resolution converted image resulting from the resolution conversion of the input image on the basis of the coefficient set selected by the coefficient selecting unit and plural pixel values contained in the input image.

Abstract: An image processing apparatus generates a sub-self-similar set F, which is a subset of a self-similar set A with respect to contraction maps f1, . . . , fn and forms an image expressing the sub-self-similar set F. The apparatus includes a base-address-set designating section, a generation-rule acquiring section and a sub-self-similar set generating section. The base-address-set designating section selects m addresses each of which formed of infinite sequence of {1, . . . , n} and generates a base address set M including the selected addresses. The generation-rule acquiring section acquires a rule of generating a hypothetical sub-self-similar set G, which is a subset of a hypothetical self-similar set B with respect to n hypothetical contraction maps g1, . . . , gn, by using the generated base address set M. The sub-self-similar set generating section generates a sub-self-similar set F, which is a subset of the self-similar set A.

Abstract: An image processing apparatus to perform an enlarging process for an original image constituted by C colors (C?2) includes a target color selecting unit that selects two target colors C1 and C2 for each local region of the original image, a sorting unit that sorts the local region on the basis of a layout of the target colors selected by the target color selecting unit, and a processing unit that determines pixel values after enlargement from the target colors C1 and C2 in accordance with a result of the sorting performed by the sorting unit.

Abstract: A first image enlargement processing section enlarges an original image to a specified size to generate an initial enlarged image. A domain block extraction section extracts a domain block image from the original image. A range block extraction section extracts a range block image from the neighborhood of the correspondence part of the domain block image in the initial enlarged image. A reduced range block preparation section reduces the range block image to the domain size to generate a reduced range block image. An enlarged range block preparation section enlarges the most similar range block image having the highest degree of similarity to an enlargement size to generate an enlarged pseudo domain block image. An enlarged image acquisition section 676 uses each enlarged pseudo domain block image to generate an enlarged image of the original image.

Abstract: An image processing apparatus includes an information acquiring portion that acquires information on image process conditions for processing image data, a creating portion that creates additional image data, serving as a watermark image, with additional information to be embedded into the image data on the basis of the information on the image process conditions acquired, and a merging portion that merges the image data with the additional image data to create composite image data.

Abstract: A domain block extracting unit extracts a domain block image from an original image. A range block extracting unit extracts a range block image from an area in the vicinity of the domain block image. The range block image has size being larger than a domain size and being smaller than an enlarged size. A reduced range block forming unit reduces the range block image to the domain size to produce a reduced range block image. A similarity judging unit compares each of the reduced range block images with the domain block image to select the highest similarity range block image. An enlarged range block forming unit forms an enlarged range block image by enlarging the size of the highest similarity range block image to an enlarged size thereof. An enlarged image acquiring unit produces an enlarged image of an original image by employing the respective enlarged range block images.

Abstract: A domain block image is extracted from an original image by a domain block extracting section, and the domain block image is classified by a domain block classifying section. A range block extracting section extracts a range block image larger than the domain block image from the original image, and a reduced range block forming section reduces the range block image at the same size as the domain block image. A similarity degree judging section judges a similarity degree between the reduced range block image and the domain block image, and an improved domain block forming section performs a conversion of pixel values with respect to the reduced range block image in accordance with this similarity degree. Further, an edge enhancement processing section executes an edge enhancement processing as to the step edge portion so as to obtain an improved domain block image.

Abstract: A first image enlargement processing section enlarges an original image to a specified size to generate an initial enlarged image. A domain block extraction section extracts a domain block image from the original image. A range block extraction section extracts a range block image from the neighborhood of the correspondence part of the domain block image in the initial enlarged image. A reduced range block preparation section reduces the range block image to the domain size to generate a reduced range block image. An enlarged range block preparation section enlarges the most similar range block image having the highest degree of similarity to an enlargement size to generate an enlarged pseudo domain block image. An enlarged image acquisition section 676 uses each enlarged pseudo domain block image to generate an enlarged image of the original image.

Abstract: A domain block extracting unit extracts a domain block image from an original image. A range block extracting unit extracts a range block image from an area in the vicinity of the domain block image. The range block image has size being larger than a domain size and being smaller than an enlarged size. A reduced range block forming unit reduces the range block image to the domain size to produce a reduced range block image. A similarity judging unit compares each of the reduced range block images with the domain block image to select the highest similarity range block image. An enlarged range block forming unit forms an enlarged range block image by enlarging the size of the highest similarity range block image to an enlarged size thereof. An enlarged image acquiring unit produces an enlarged image of an original image by employing the respective enlarged range block images.