Abstract: An image-capturing system diagnostic device includes: an image acquisition unit that obtains an image; and a monitoring unit that monitors a quantity of foreign matter present in an optical path by generating defect information indicating a defect at pixels caused by the foreign matter in the optical path based upon the image obtained by the image acquisition unit and calculating an areal ratio of defective pixels in the image based upon the defect information having been generated and issues a warning for a photographer if the areal ratio of the defective pixels exceeds a predetermined value.

Abstract: An image processing method for converting a first image, which is expressed in a calorimetric system made up of a plurality of color components and is constituted of a plurality of pixels each holding color information corresponding to a single color component, to a second image constituted with a plurality of pixels all holding color information corresponding to at least one common color component, includes: a color difference information generation step in which color difference information is generated by using color information in the first image; a color gradient analysis step in which a color gradient indicating an extent of color change is determined based upon the color difference information having been generated; and an image conversion step in which the first image is converted to the second image based upon the color gradient having been determined.

Abstract: An image processing method for removing a noise component contained in an original image includes: smoothing a noise component contained in an original image on a temporary basis by using a noise fluctuation index value; extracting a temporary noise component free of a non-noise component based upon a differential signal representing a difference between the original image and a smoothed image; extracting an actual noise component by further excluding a component less likely to be a noise component from the extracted temporary noise component by comparing the extracted temporary noise component with the noise fluctuation index value again; and removing noise from the original image based upon the extracted actual noise component having been extracted.

Abstract: An image processing method for removing a noise component contained in an original image, includes: separating an original image into a temporary noise-free image and a temporary noise component; extracting an edge component in the temporary noise-free image by executing edge detection on the temporary noise-free image; determining a fine edge component in the original image contained in the temporary noise component based upon a level of the extracted edge component; extracting an actual noise component by excluding the fine edge component from the temporary noise component; and removing noise from the original image based upon the extracted actual noise component.

Abstract: An image-capturing system diagnostic device includes: an image acquisition unit that obtains an image; and a monitoring unit that monitors a quantity of foreign matter present in an optical path by generating defect information indicating a defect at pixels caused by the foreign matter in the optical path based upon the image obtained by the image acquisition unit and calculating an areal ratio of defective pixels in the image based upon the defect information having been generated and issues a warning for a photographer if the areal ratio of the defective pixels exceeds a predetermined value.

Abstract: An image processor captures image data which include at least correction object color components and reference color components and has one kind of color component per pixel. The image processor acquires or detects information about positional shifts of the correction object color components and corrects positional shifts of correction object color components. In this correction, image structures lost from correction object color components are compensated for by image structures extracted from reference color components.

Abstract: An image processing method for converting a first image that is expressed in a colorimetric system made up of a plurality of color components and comprises a plurality of pixels each having color information corresponding to one of the color components into a second image that comprises a plurality of pixels each having at least a common type of color information, includes: a color judgment step that includes a color difference information generation step in which color difference information is generated for a processing target pixel in the second image by using color information in the first image through one of at least three different methods and a color evaluation step in which a color evaluation is individually executed for each of processing target pixels in the second image by using the color difference information; and an image conversion step in which the first image is converted to the second image based upon results of the color evaluation executed in the color judgment step.

Abstract: An image processing apparatus includes a discriminating unit that discriminates a color component originating in an image structure in an image captured through an optical system from a color component attributable to a chromatic aberration of the optical system, and a correction unit that corrects the color component attributable to the chromatic aberration of the optical system based upon discrimination results provided by the discriminating unit.

Abstract: An image processing device that converts a first image captured via an optical system in which at least one of a plurality of color components is missing in one pixel and MTF characteristics are different between a reference color component and at least one missing color component at an imaging plane, into a second image in which MTF characteristics are matched, includes: an image creation unit that acquires information concerning differences in MTF characteristics between the missing color component and the reference color component in a pixel having the missing color component of the first image and creates the second image by using the acquired information.

Abstract: An image processing method adopted to remove noise present in an image, includes: an image input step in which an original image constituted of a plurality of pixels is input; a multiple-resolution images generation step in which a plurality of band-limited images with resolutions decreasing in sequence are generated by filtering the input original image; a first noise removal step in which virtual noise removal processing is executed individually for each of the band-limited images; a second noise removal step in which actual noise removal processing is executed for the individual band-limited images based upon the band-limited images from which noise has been virtually removed through the first noise removal step; and an image acquisition step in which a noise-free image of the original image is obtained based upon the individual band-limited images from which noise has been actually removed through the second noise removal step, and the virtual noise removal processing executed in the first noise removal s

Abstract: An image processing method adopted to remove noise present in an image, includes: an image input step in which an original image constituted of a plurality of pixels is input; a multiple resolution image generation step in which a plurality of low-frequency images with resolutions decreasing in sequence and a plurality of high-frequency images with the resolutions decreasing in sequence are generated by decomposing the input original image; a noise removal processing step in which noise removal processing is individually executed on the low-frequency images and the high-frequency images; and an image acquisition step in which a noise-free image of the original image is obtained based upon both the low-frequency images and the high-frequency images having undergone the noise removal processing.

Abstract: An image processing method for converting a first image, which is expressed in a calorimetric system made up of a plurality of color components and is constituted of a plurality of pixels each holding color information corresponding to a single color component, to a second image constituted with a plurality of pixels all holding color information corresponding to at least one common color component, includes: a color difference information generation step in which color difference information is generated by using color information in the first image; a color gradient analysis step in which a color gradient indicating an extent of color change is determined based upon the color difference information having been generated; and an image conversion step in which the first image is converted to the second image based upon the color gradient having been determined.

Abstract: An image processing method for removing noise contained in an image includes: inputting an original image constituted with a plurality of pixels; generating a plurality of band-limited images, resolution levels of which are lowered in sequence, by executing a specific type of band pass filter processing on the original image; extracting a high-frequency component from each of the band-limited images by executing high-pass filter processing on the band-limited images; extracting a noise component contained in each of the band-limited images by separating the noise component through nonlinear conversion processing executed on the extracted high-frequency component; and removing the noise in the original image based upon the extracted noise component in each band-limited image.

Abstract: An image processing method for converting a first image, which is expressed in a colorimetric system made up of a plurality of color components and is constituted of a plurality of pixels each holding color information corresponding to a single color component, to a second image constituted with a plurality of pixels all holding color information corresponding to at least one common color component, includes: a color difference information generation step in which color difference information is generated by using color information in the first image; a color gradient analysis step in which a color gradient indicating an extent of color change is determined based upon the color difference information having been generated; and an image conversion step in which the first image is converted to the second image based upon the color gradient having been determined.

Abstract: To acquire the signal values of all the color components (RGB) at the positions of all the pixels constituting an image, the processing for interpolating the signal value of a lacking color component is performed by converting the gradation space from a linear gradation space into a square root gradation space with offset as follows. An offset ? in proportion to the ISO sensitivity preset for an imaging device is added to a linear gradation signal x. The value (x+?) after the offset is converted into a gamma space of one-half power. Therefore, the errors contained in the signal values after the gamma conversion are equalized over the whole gradation by the error propagation rule. The slope of the curve 23 indicating the square-root gradation space with offset is not steeper in a region (e.g. 0<x<0.1) where the linear input is smaller than that of the curve 22 indicating the mere square-root gradation space.

Abstract: An image processing method includes: inputting color image data obtained by capturing an image at a given imaging sensitivity level; and converting the color image data to a specific uniform color space determined in correspondence to the imaging sensitivity level.

Abstract: A first interpolation processing apparatus that engages in processing on image data which are provided in a colorimetric system constituted of first˜nth (n?2) color components and include color information corresponding to a single color component provided at each pixel to determine an interpolation value equivalent to color information corresponding to the first color component for a pixel at which the first color component is missing, includes: an interpolation value calculation section that uses color information at pixels located in a local area containing an interpolation target pixel to undergo interpolation processing to calculate an interpolation value including, at least (1) local average information of the first color component with regard to the interpolation target pixel and (2) local curvature information corresponding to at least two color components with regard to the interpolation target pixel.

Abstract: An image processing method for filtering image data, which is constituted with a plurality of pixels, at each pixel position by using pixel values indicated by pixels present within a predetermined range containing a target pixel, includes: determining two arguments that are a first argument defined by a spatial distance from the target pixel and a second argument defined by a difference in signal intensity relative to the target pixel, in correspondence to each of the pixels present within the predetermined range; obtaining a weighting coefficient to be used when filtering each of the pixels present within the predetermined range, based upon a single integrated argument represented by a product of the first argument and the second argument; and filtering the image data by using a filter coefficient corresponding to the weighting coefficient having been obtained.

Abstract: An image processing unit of the present invention receives a first image, performs weighted addition on color information in the first image to generate a color component different from that of the color information in the first image, and outputs the generated color component as a second image. The first image is expressed in a plurality of color components and comprises a plurality of pixels each having color information corresponding to one of the color components. At least nine coefficient patterns consisting of values of not less than zero are prepared, and any one of the coefficient patterns is used for weighted addition. This allows an improvement in image quality with high precision.

Abstract: The present invention is intended to record image data having a wide dynamic range is a file together with image data having a narrow dynamic range. First, an image recording apparatus separately gradation-converts image data to be recorded into primary data having a narrow dynamic range and secondary data having a wide dynamic range. Then, the image recording apparatus calculates data that determines correlation between the primary data and secondary data and employs the calculated data as tertiary data. The image recording apparatus records the primary data and the tertiary data in a file. On the other hand, an image reproducing apparatus reads out primary data and tertiary data that were recorded in the above manner and reproduces secondary data having a wide dynamic range based on the primary data and the tertiary data.