Abstract: 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.

Abstract: Technology is known for correcting the gradation characteristics of an input image signal in accordance with the characteristics of a display device, but a correction that is suitable for the usage of the display device is desired. Provided is an image processing apparatus including a first gradation converting section that converts a gradation of an image signal input thereto; a sharpening process section that performs a sharpening process on the image signal after the gradation has been converted by the first gradation converting section; a second gradation converting section that converts the gradation of the image signal after the sharpening process has been performed; and a display control section that displays an image indicated by the image signal after the gradation has been converted by the second gradation converting section, in a display device.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Technology is known for correcting the gradation characteristics of an input image signal in accordance with the characteristics of a display device, but a correction that is suitable for the usage of the display device is desired. Provided is an image processing apparatus including a first gradation converting section that converts a gradation of an image signal input thereto; a sharpening process section that performs a sharpening process on the image signal after the gradation has been converted by the first gradation converting section; a second gradation converting section that converts the gradation of the image signal after the sharpening process has been performed; and a display control section that displays an image indicated by the image signal after the gradation has been converted by the second gradation converting section, in a display device.

Abstract: 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.

Abstract: 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 L2 norm of a coefficient matrix ? 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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 L2 norm of a coefficient matrix ? 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.

Abstract: 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.