Importance

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Abstract

Traditionally, the operator must determine the type of an image displayed on a screen and manually select one of various kinds of effect processing for the type of the image. As is generally known, however, such operations have a lack of accuracy and are difficult for an untrained user to carry out. In addition, the image is not correctly compensated for color slippages over the entire gradation range. Furthermore, in the case of image data including an abnormal element other than just a color slippage, the image can not be corrected with a high degree of efficiency. At a step S102, a sample-count distribution of image data is found for each color component by applying a thinning technique on samples. At a step S116, a judgment as to whether or not analogy exists among the sample-count distributions of the color components is formed. A low degree of analogy is regarded as an indicator which suggests that characteristics recognized from the sample-count distributions shall naturally be made uniform among the color components. In this case, the characteristics are compensated for a color slippage included therein by correcting an offset, putting an emphasis on the contrast and correcting the brightness at steps S204 to S216 in order to produce a well pitched and good image from the image data with poor color reproducibility. In addition, since the compensation and correction work is automated, even an untrained user is capable of correcting the balance of color with ease. Furthermore, at a step S205, an offset quantity reflecting a degree of analogy is calculated for use in the compensation of the characteristics for a color slippage.

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First Claim