Abstract: When an acquired image file GF includes image processing control information GI, a CPU executes image quality adjustment of image data GD in an image processing mode GM specified by the image processing control information GI. When the acquired image file GF does not include the image processing control information GI, on the other hand, the CPU retrieves Exif information and in the case of successful retrieval of the Exif information, selects the image processing mode GM based on the Exif information and executes image quality adjustment of the image data GD in the selected image processing mode GM. In the case where a selected shooting mode is described in the Exif information, the selected shooting mode is used for the selection of the image processing mode GM. In the case where no selected shooting mode is described in the Exif information, on the other hand, another shooting condition is used for the selection of the image processing mode GM.

Abstract: When an acquired image file GF includes image processing control information GI, a CPU executes image quality adjustment of image data GD in an image processing mode GM specified by the image processing control information GI. When the acquired image file GF does not include the image processing control information GI, on the other hand, the CPU retrieves Exif information and in the case of successful retrieval of the Exif information, selects the image processing mode GM based on the Exif information and executes image quality adjustment of the image data GD in the selected image processing mode GM. In the case where a selected shooting mode is described in the Exif information, the selected shooting mode is used for the selection of the image processing mode GM. In the case where no selected shooting mode is described in the Exif information, on the other hand, another shooting condition is used for the selection of the image processing mode GM.

Abstract: The present invention is an image file selection method of selecting multiple image files available for composing a panoramic image from a plurality of image files including image data and image attribute information which includes positional information representing a geographical position at a time of photographing. The method includes the steps of: (a) reading out the positional information from each of the plurality of image files; and (b) selecting multiple image files photographed at geographical positions within a predetermined distance as the multiple image files available for composing the panoramic image based on the positional information.

Abstract: In case where photo information PI (Exif IFD) is included in image data GF, a CPU calculates a modified contrast correction amount tCurve_cont and a modified brightness value correction amount tCurve_Y, in consideration of an exposure correction amount (a light exposure) EV. The CPU applies the obtained modified contrast correction amount tCurve_cont and the modified brightness value correction amount tCurve_Y to a tone curve, and executes an adjustment of image quality including contrast and brightness value. In other words, the CPU modifies characteristics of the tone curve by using the modified contrast correction amount tCurve_cont and the modified brightness value correction amount tCurve_Y, and adjusts the image quality of the image data by applying the modified tone curve to the image data GD.

Abstract: It is received first image data described on the basis of a first color space. It is acquired color space converting information adapted to be used to convert the first image data into second image data described on the basis of a prescribed second color space. The first image data is converted into the second image data in accordance with the color space converting information. A prescribed feature quantity is extracted from the second image data.

Abstract: A technology is provided whereby correction may be carried out appropriately for both a person's face and other portions of an image, when performing color correction for image data of a photographic image in which a person appears. A process such as the following is carried out during color correction of image data of a photographic image. First, the image data of the photographic image is analyzed, and a first region which is part of the photographic image and in which a person's face is present is determined. Then, on the basis of the portion corresponding to the first region of the image data, a first parameter relating to color is calculated. On the basis of part of the image data corresponding to a second region which is part of the photographic image but different from the first region, a second parameter relating to color is calculated. The color tone of the data is then corrected on the basis of the first and second parameters.

Abstract: It is received first image data described on the basis of a first color space. It is acquired color space converting information adapted to be used to convert the first image data into second image data described on the basis of a prescribed second color space. The first image data is converted into the second image data in accordance with the color space converting information. A feature quantity is extracted from the second image data. A correction table is generated based on the feature quantity so as to include a correspondence between the second image data and third image data. The second data is corrected with reference to the correction table to generate the third image data. The third image data is converted into fourth image data described on the basis of a third color space adapted to be used to generate an image.

Abstract: It is received image data obtained by capturing an image. The image data is compared with a prescribed criterion for judging whether the image includes a prescribed part of a human, and it is extracted a part of the image that is asserted as a part including the prescribed part of the human with a matching degree with respect to the criterion. The extracted part of the image is corrected in accordance with the matching degree to obtain corrected image data.

Abstract: An image of a first image data PID is reduced to generate second image data PID2. The second image data PID2 is analyzed. A lookup table 104a is generated based on the analysis. The lookup table 104a is a table for image conversion that alters at least part of color of image data. The first image data is converted by referencing the lookup table 104a.

Abstract: Color balance correction value is calculated based on an average pixel value of specific color pixels if an average hue of high luminance pixels is not within a predetermined range in the vicinity of a specific chromatic color (for example, skin color). This calculation may additionally use a specific color pixel ratio as well as the average pixel value of the specific color pixels. On the other hand, if the average hue of high luminance pixels is within the predetermined range in the vicinity of a specific chromatic color (for example, skin color), the color balance correction value is calculated using the average pixel value of the plurality of high luminance pixels, without using the average pixel value of the specific color pixels.

Abstract: An image processing technology to correct pixel values of input pixels is provided. First, a conversion relationship indicating the relationship between input pixel values and first tone-corrected values obtained by correction of the input pixel values is established. Based on this conversion relationship, the input pixel values are then converted to first tone-corrected values having a higher number of bits than the input pixels. From the first tone-corrected values, second tone-corrected values having a smaller number of bits than the first tone-corrected values are then generated. During this process, the second tone-corrected values is generated such that a tone of the first tone-corrected values is reproduced by multiple second tone-corrected values for multiple mutually adjacent pixels.

Abstract: An image processing apparatus executes color balance correction of an image composed of multiple pixels. The image processing apparatus comprises a representative value calculation unit and a correction processor. The representative value calculation unit calculates, based on signal values of the pixels included in a skin tone area that includes pixels indicating human skin within the image, a representative value representing hue and chroma of the pixels included in the skin tone area. The correction processor executes color balance correction of the image using execution correction amount set based on normal correction amount obtained by multiplying a difference between the representative value and an ideal value designated as a value representing ideal hue and chroma of human skin by a reduction coefficient. The value of the reduction coefficient is set such that the value of the reduction coefficient can vary in response to the representative value.

Abstract: This arrangement of the invention makes intuitively comprehensible image correction of RGB color image data after conversion to HSI data in an intuitive HSI expression format, while ensuring no substantial change of the picture quality of a resulting color image by correction. The technique of the invention analyzes an image consisting of sampling HSI data with regard to each of multiple memory colors, that is, flesh color, green, and sky blue, and sets color correction areas as object correction ranges and correction rate curves in the color correction areas in respective hue ranges of the multiple memory colors, based on the results of the image analysis. These settings are given in the form of a correction table.

Abstract: The technique of the invention accurately detects a pixel defect in an image taken by an imaging device, such as a digital still camera. The image processing flow of the invention maps luminance data to respective pixels of a specified pixel array and computes a difference between the luminance data of each target pixel and an average value of the luminance data of four adjoining pixels on the top, bottom, left, and right of the target pixel. The presence or the absence of any pixel defect is detected according to the computed difference. The luminance data of an identified defective pixel detected as the pixel defect is corrected with the luminance data of adjoining pixels on the top, bottom, left, and right of the identified defective pixel.

Abstract: An image quality adjuster adjusts luminance values of image data sing the image data generated by an image generating device, and image generation record information associated with the image data containing at least light emission information for a supplemental light source flash at the time of generation of the image data. Specifically, a decision is made based on the light emission information for the supplemental light source as to whether to execute an image quality adjustment process; and if a decision to do so, the image data is adjusted so as to reduce the maximum luminance value, which is the largest possible luminance value the image data may have.

Abstract: There is provided an output device for outputting an image using image data generated by an image generating device, and image generation record information that is associated with the image data and that includes at least information relating to shooting conditions at the time of generation of the image data, comprising an image quality adjuster that, in the event that the image generation record information contains light source information relating to color shift of a light source at the time of generation of the image data, is able to execute the white balance adjustment process of the image data on the basis of the color of the light source obtained using the light source information; and an image output unit for outputting an image according to the image quality-adjusted image data.

Abstract: A CPU 411 divides image data GD into a plurality of areas (pixel data groups), analyzes the data in image data area units, and determines the color value and dispersion value of the image data areas. When the determined color value is within a flesh toned color area and the dispersion value is at or below a reference dispersion value, the CPU 411 determines the target image data area to be a flesh area. The CPU 411 carries out a smoothing process on the image data area determined to be a flesh area.

Abstract: A CPU 111 acquires monochromatic output image processing conditions including the RGB channel mix rate from ROM 113 using set photograph scenes. When no command for setting the photograph scene has been input, the CPU 111 analy8zes the color image data to generate monochromatic output image processing conditions including the RGB channel mix rate. The CPU 111 generates image process control data using the set monochromatic output image processing conditions, and associates the generated image processing control data with the color image data for output.

Abstract: A CPU 231 calculates modified brightness correction amount tCurve_Y with consideration of exposure correction amount (or exposure value) EV if photography information PI (or Exif IFD) is included in image data GF. Specifically, the modified brightness correction amount tCurve_Y is calculated by dividing original brightness correction amount tCurve_Yorg by 2|EV|. Therefore, it decreases in geometrical progression as the exposure correction amount increases. The CPU 231 applies the obtained modified brightness correction amount tCurve_Y to a tone curve to adjust image quality including brightness. More specifically, it uses the modified brightness correction amount tCurve_Y to modify the characteristics of the tone curve, and then uses the modified tone curve to adjust the image quality of the image data.

Abstract: A CPU 200 acquires image data of a photographed image, determines a specific subject area containing a specific subject in the photographed image, and calculates a specific subject characteristic value for representing a characteristic of image data corresponding to the determined specific subject area.