A computer includes an image processing apparatus, the image processing apparatus includes a transformation unit that transforms color information on an input image signal on the basis of a transformation rule; a correction range calculation unit that calculates a correction range in a predetermined color space on the basis of a positional relationship between source coordinates and destination coordinates in the color space; and a point-based transfer distance calculation unit that calculates transformation destination coordinates at respective points within the correction range on the basis of the positional relationship between the source coordinates and the destination coordinates, and a positional relationship between coordinates at the respective points within the correction range and the source coordinates to reflect the calculated transformation destination coordinates on the transformation rule.

A computer includes an image processing apparatus, the image processing apparatus includes a transformation unit that transforms color information on an input image signal on the basis of a transformation rule; a correction range calculation unit that calculates a correction range in a predetermined color space on the basis of a positional relationship between source coordinates and destination coordinates in the color space; and a point-based transfer distance calculation unit that calculates transformation destination coordinates at respective points within the correction range on the basis of the positional relationship between the source coordinates and the destination coordinates, and a positional relationship between coordinates at the respective points within the correction range and the source coordinates to reflect the calculated transformation destination coordinates on the transformation rule.

An image processing apparatus configured to correct at least part of a face image has an image acquisition unit that acquires an input image, a region extraction unit that extracts a pupil region, which is a region corresponding to an eye of a person, from the input image, a pixel extraction unit that extracts a pixel from the pupil region whose brightness value is higher than a threshold value, a determination unit that determines, based on the result of extraction performed by the pixel extraction unit, whether or not halation has occurred in the pupil region, and a correction unit that performs, based on the result of determination performed by the determination unit, processing for correcting halation on the pupil region. The pixel extraction unit sets the threshold value based on a bias of a brightness distribution of the pixels included in the pupil region.

A skin color image gamut weight detecting method and a device thereof are provided. The method includes: receiving an image including first color components and second color components; obtaining a skin color region, a skin color category, and a first gamut; obtaining first color component values and first cardinal numbers according to the first color components; obtaining second color component values and a plurality of second cardinal numbers according to the second color components; obtaining a second gamut and a weight center according to the skin color category, the first cardinal numbers, the second cardinal numbers, the first color component values, and the second color component values; obtaining a first weight area and a second weight area according to the first gamut and the second gamut; and obtaining a skin color gamut weight map according to the weight center, the first weight area, and the second weight area.

An amount of color correction of a facial region is modified based on changes caused in face average values by white balance correction. Also, the amount of color correction of the facial region is modified according to luminance of pixels of interest to perform optimum color correction on the facial region and a highlight region.

An amount of color correction of a facial region is modified based on changes caused in face average values by white balance correction. Also, the amount of color correction of the facial region is modified according to luminance of pixels of interest to perform optimum color correction on the facial region and a highlight region.

A method for harmonizing colors of an original image is disclosed. The method comprises: computing a saliency map of the original image, for each of a plurality of color harmonic schemes: determining a temporary harmonized image from the original image according to the current color harmonic scheme, computing a saliency map of the temporary harmonized image, comparing the saliency map of the original image and the saliency map of the temporary harmonized image, in order to obtain a saliency comparison result, computing a corrected color comparison result from colors of the original image, colors of the current color harmonic scheme and the saliency comparison result, selecting, as the harmonized image, the temporary harmonized image obtained with the color harmonic scheme minimizing the corrected color comparison result.

A method for harmonizing colors of an original image is disclosed. The method comprises: computing a saliency map of the original image, for each of a plurality of color harmonic schemes: determining a temporary harmonized image from the original image according to the current color harmonic scheme, computing a saliency map of the temporary harmonized image, comparing the saliency map of the original image and the saliency map of the temporary harmonized image, in order to obtain a saliency comparison result, computing a corrected color comparison result from colors of the original image, colors of the current color harmonic scheme and the saliency comparison result, selecting, as the harmonized image, the temporary harmonized image obtained with the color harmonic scheme minimizing the corrected color comparison result.

An image processing apparatus comprises an image acquiring unit configured to acquire an image; a representative-color acquiring unit configured to acquire a representative color, which is a color representing a target region where the correction is performed, from the acquired image; and an image correcting unit configured to perform correction processing on the image on the basis of a set reference color, wherein the image correcting unit updates the reference color with the representative color when similarity between the representative color corresponding to the processing target image and the reference color is equal to or smaller than a predetermined threshold, and does not update the reference color when the similarity is larger than the predetermined threshold.

An image processing apparatus comprises an image acquiring unit configured to acquire a first image, which is an image including an eye; an image generating unit configured to generate a second image, which is a binary image representing an edge of the first image; a classifying unit configured to classify, based on presence or absence of the edge, pixels included in the second image; and a pupil-region generating unit configured to generate a pupil region, which is a region corresponding to a pupil in the first image, based on a classification result, wherein when pixels having a same value are present separately in a plurality of blocks in the second image, the classifying unit performs the classification of the pixels further based on areas of the blocks or luminance values of pixels in the first image corresponding to the blocks.