Eizo Gmbh

Masafumi Higashi

Reo Aoki

Haifeng Chen

Takashi Nakamae

Hiroki Matsuzaki

Mamoru Ogaki

Masashi Nakao

Yuya Yoshida

Yu Kato

Tadayoshi Katagiri

Naoaki Hirata

Yusuke Bamba

Ikumi Arai

Keita Hashi

Reo Abe

Takuya Matsuda

Noriyuki Hashimoto

Lei Zhu

The present invention has been made in view of the foregoing, and an object thereof is to provide a method for learning a threshold that can provide a more objective threshold applied to pixels in the mammography image. The present invention provides a method for learning a threshold value applied to pixels in a mammography image comprising: an acquiring step; and a learning step, wherein in the acquiring step, the mammography image is acquired, in the learning step, a relationship between the mammography image and a mammary gland pixel estimation threshold is learned, the mammary gland pixel estimation threshold is a threshold value used to calculate a mammary gland pixel area of each pixel of a mammary gland region in the mammography image, and the mammary gland pixel area is a value indicating a degree of a mammary gland pixel-likeness of the pixel in the mammography image.

Method for learning threshold value

The present invention has been made in view of the foregoing, and an object thereof is to provide an information processing device capable of appropriately determining a necessity of the ultrasonography even when a high-density mammary gland area exists in a narrow area. The present invention provides an information processing device comprising: a mammary gland area extractor configured to extract a mammary gland area in a mammography image; a mammary gland pixel detector configured to detect a mammary gland pixel in the mammary gland area; and a mammary gland density calculator configured to calculate a mammary gland density based on a ratio of the mammary gland pixels to the mammary gland area, wherein the mammary gland area is a narrower area than an entire breast in the mammography image.

Information processing device, information processing method, and computer program

Provided is an image processing device, image display device, and program that allow an image captured by an imaging device not having a vibration suppression function or an image whose vibration has been suppressed incompletely to be displayed on a display device with the vibration suppressed. The image processing device includes a motion estimator configured to estimate the amount of motion of an object between a first image and a second image later than the first image and a motion compensator configured to perform a conversion process on the second image so that vibration of the object between the first image and the second image is suppressed, on the basis of the amount of motion of the object. The motion estimator has a first estimation mode in which the amount of motion of the object is estimated in a predetermined search area and a second estimation mode in which the amount of motion of the object is estimated in a larger area than the search area in the first estimation mode.

Image processing device, image display device, and program

An image processing device, an image processing method, and an image processing program capable of outputting an image with appropriate sharpness for an input image that may include both a dynamic region and a static region. An image processing device includes a static and dynamic information calculator configured to calculate static and dynamic information of an input image; a blend ratio setting unit configured to determine a blend ratio by performing a predetermined operation on the static and dynamic information of the input image; and an image processing unit configured to generate an output image optimized for static and dynamic change by performing image processing on the input image on the basis of the blend ratio.

Image processing device, image processing method, and image processing program for maintaining sharpness of image

Provided are an information processing apparatus and program that are able to improve representable gradations in a pseudo manner while reducing flicker including a random number generator configured to generate a random number sequence; a comparator configured to make a comparison between a threshold and a random number value, the threshold being associated with any number of lower bits, the any number of lower bits forming input image data with any number of upper bits, the random number value forming the random number sequence.

Information processing apparatus and program

Provided is an image conversion method that allows for the representation, on a display, the light and shade of a printed image obtained by printing the image on paper. The image conversion method includes a step of acquiring an illumination-light component and a reflectance component from an input image, a step of correcting the illumination-light component in accordance with display luminance information of a print mode in which the input image is to be printed, so that light and shade of the input image displayed on a display come close to light and shade of a printed image obtained by printing the input image in the print mode, and a step of acquiring a combined image by combining the corrected illumination-light component and the reflectance component or the corrected reflectance component.

Image conversion method

Provided is an image combination method that can represent the texture of a drawing medium such as paper without causing a foreground fading problem. The image combination method includes a step of acquiring an illumination-light component and a reflectance component from an input image, a step of generating a texture-combined image by combining the reflectance component or the corrected reflectance component and a texture image representing a desired texture, and a step of acquiring a combined image by combining the illumination-light component or the corrected illumination-light component and the texture-combined image.

Combining drawing media texture and image data for display while maintaining the dynamic range of the original image

An image converting method and image converting device that are able to properly reproduce the appearance of the original image even in an environment having different brightness. The image converting method includes a JND corresponding value width acquisition step of, on the basis of input image data, acquiring a JND corresponding value width corresponding to a reflectance component of the input image data, a luminance width acquisition step of acquiring a luminance width corresponding to the JND corresponding value width or a value obtained by converting the JND corresponding value width in accordance with a predetermined rule using, as a reference, a second reference luminance different from a first reference luminance.

Image converting method and device

A technique to remove fog from an image more appropriately has been called for. An image processing system is provided, including: a luminance evaluation value deriving unit that derives a luminance evaluation value of an at least partial region of an image; a saturation evaluation value deriving unit that derives a saturation evaluation value of the at least partial region of the image; a contrast evaluation value deriving unit that derives a contrast evaluation value of the at least partial region of the image; and a haze depth estimating unit that derives a haze depth estimate value of the image based on the luminance evaluation value, the saturation evaluation value, and the contrast evaluation value.

Image processing system and computer-readable recording medium

Improving the visibility of the dark portion and to prevent the degradation of image quality caused by excessive correction. A reflectance calculation unit is storing a parameter RGain for adjusting the amplitude of a reflectance component R. An illumination light correction unit generates a corrected illumination light component L1 from an illumination light component L and a formula L1=(log(LAmp*L+1))/(log(LAmp+1)). An image resynthesis unit obtains a corrected illumination light component L' from L&#x2032;=LGain*L1+(1&#x2212;LGain)*L. The image resynthesis unit also calculates a corrected image Iout from the corrected illumination light component L&#x2032; and the corrected reflectance R&#x2032;, as well as from a formula Iout=exp(log L&#x2032;+RGain(log I&#x2212;log L)). The value of the corrected illumination light component (L&#x2032;) is determined based on the ratio (LGain) at which the output value of the correction function (L1) and the original illumination light component (L) are combined.

Device or method for displaying image

A technique to remove fog from an image more appropriately has been called for. An image processing system is provided, including: a haze depth estimating unit that derives a haze depth estimate value of one frame among a plurality of frames included in a moving image; a parameter adjusting unit that adjusts a parameter to be used in a haze removal process of the one frame based on a haze depth estimate value of the one frame, and a relationship between the one frame and a past frame of the one frame; and a haze removing unit that executes a haze removal process on the one frame based on the parameter adjusted by the parameter adjusting unit.

A technique to remove fog from an image more appropriately has been called for. An image processing system is provided, including: a high saturation pixel extracting unit that extracts, from one frame among a plurality of frames included in a moving image, a high saturation pixel having a saturation higher than a predetermined threshold; a high saturation pixel rate deriving unit that derives a high saturation pixel rate indicative of a percentage of the high saturation pixels in the one frame; and a scene change judging unit that judges whether or not a scene change is included in the moving image based on different criteria depending on whether or not the high saturation pixel rate in the one frame is higher than a predetermined threshold.

An image quality enhancing apparatus which make a learning-type image quality enhancing method utilizing a sparse expression practical are provided. The apparatus calculates, from the feature quantity of an image, coefficients of low-image-quality base vectors expressing a feature quantity with a linear sum and generates the image with the image quality enhanced by calculating a linear sum of high-image-quality base vectors using the calculated coefficient. When calculating the coefficient, the number of base vectors with non-zero coefficients is determined, the determined number of base vectors is selected, and a solution of a coefficient matrix is calculated by assuming the coefficients of the base vectors other than the selected base vectors are zero. The amount of processes necessary for obtaining a sparse solution of a coefficient matrix can be reduced by adjusting the number of base vectors with non-zero coefficients, and a practical image quality enhancing apparatus can be realized.

Image quality enhancing apparatus, image display apparatus, image quality enhancing method, and computer readable storage medium

An image quality enhancing apparatus, an image display apparatus, an image quality enhancing method, and a computer readable storage medium which make a learning-type image quality enhancing method utilizing a sparse expression practical are provided. The image quality enhancing apparatus calculates, from the feature quantity of an image, coefficients of low-image-quality base vectors expressing a feature quantity with a linear sum and generates the image with the enhanced image quality by calculating a linear sum of high-image-quality base vectors using the calculated coefficient. When calculating the coefficient, T base vectors highly influential on the feature quantity are selected from among a plurality of base vectors and an analytic solution making Lnorm of a coefficient matrix &#x3b1; as small as possible is calculated. A sparse solution of the coefficients can be obtained without using the iteration method and a practical image quality enhancing apparatus can be realized.

Color of a color image may be adjusted by a color adjustment apparatus, image display apparatus, and color adjustment method to enable easier distinction between objects shown in the image. A parameter defines a range of saturation to be adjusted within saturation before color adjustment and a range of change of the saturation after color adjustment compared to the saturation before color adjustment. The color adjustment apparatus calculates the saturation from an image signal, calculates the saturation after color adjustment according to the saturation before color adjustment such that the saturation in the range determined by the parameter increases/decreases by an amount determined by the parameter, and generates an image signal from the saturation after color change. By determining the parameter such that the saturation difference between prescribed colors is greater after color adjustment, the difference in color between a plurality of objects shown in the image is increased.

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Ishikawa, Japan

Masafumi Higashi