Abstract: A method of automatic contrast correction comprises providing digital image data, representing the data in the form of a brightness histogram, determining a measure of central tendency for said histogram, adding a shift value to the measure of central tendency to provide an adjusted measure of central tendency, using the both the determined and adjusted measures of central tendency to determine the exponent of a tone reproduction curve, and applying the tone reproduction curve to the brightness values of the image. Additionally, the method may provide further correction by applying to the brightness values of the image an S-shaped tone reproduction curve that does not change a measure of central tendency of the brightness histogram.

Abstract: A method for reducing image noise in a digital image including establishing image data of image pixel values; specifying a local virtual surface patch; fitting the local virtual surface patch to the image data; using the local virtual surface patch to estimate a palliative value of at least one pixel in the region of the local virtual surface patch; replacing an original pixel value with the palliative value.

Abstract: A method of correcting image saturation is performed by defining saturated colors in a chromaticity color space; and deriving an overall correction of the saturation of colors in the image using the defined saturation of these colors in conjunction with a table of corrections indexed by hue and lightness. This process has a unique attribute of being able to automatically decrease saturation in regions of an image where oversaturation is detected.

Abstract: Line defects are removed from an image by providing image data in digital form, analyzing segments of the image data as groups of pixels, detecting line defects in the image by application of a line detector, such as a local radial angular transform, and adjusting the image data to correct the detected line defects within the determined limits.

Abstract: A method corrects a color image by avenging at least two color channels in regions near the minimum of histograms of the at least two color channels; selecting the smallest of the avenge color values as a black point; averaging at least two color channels in regions near the maximum of the histograms of the at least two color channels and selecting the largest of the avenge color values as the white point; and correcting the at least two color channels by adjusting the smallest and the largest color averages to respectively match the valves of the black point and the white point to form corrected image data. A preferred method limits the adjustment to a predetermined amount of clipping of the at least two color channels.

Abstract: Image defects in a digital image are reduced by a process comprising providing a digital image data set in the form of a matrix of pixels; selecting a sub-matrix comprising at least a 5×5 matrix of pixels; identifying a pixel within the sub-matrix to be treated as a central pixel; determining a value for at least one optical property in the central pixel; selecting at least four pixels around the central pixel as averaging pixels, at least two of the averaging pixels being in a position in the sub-matrix that is not adjacent the position in the matrix of the central pixel; determining a value for the at least one optical property for the at least four averaging pixels; averaging the values for the at least one optical property for more than one of the at least four averaging pixels to provide an average treatment value for the central pixel; assigning the average treatment value for the central pixel to the central pixel; and storing the average treatment value assigned to the central pixel.

Abstract: A computer with a monitor viewable program executes to display a histogram of image data on the monitor. The monitor contemporaneously displays a screen image viewed on a monitor of the histogram, and displays a digital or analog control element that controls both compression and expansion of midtones. Activation of the midtone compression/expansion element alters the displayed image according to effects of programs underlying the control of the element. This histogram display and element are associated on a single logical screen display in which at least one other image data modification effect is present on the screen image as an addressable image data modification effect.

Abstract: A method of reducing artifacts in an image previously processed by block transform encoding may comprise the steps of: determining block boundaries; determining an approximate metric of artifact visibility; optionally interpolating across block boundaries; adaptively filtering luminance; optionally adaptively filtering chrominance; adaptively adjusting local saturation variation; and adaptively simulating high spatial frequency image detail; wherein the adaptive steps are executed to an extent or in an amount depending on the metric or standard or measurement of artifact visibility.

Abstract: After identification of an image or image area where correction is to be effected for red-eye defects, and identification of eye regions within the image or the image area, color data from the area is provided, collected or analyzed according to color channel information. The color channel information may be defined for specific or collections of wavelength values or color content values, usually with at least two channels, up to four or more color channels used to carry all of the information (and with digital images, pixel information) for each color. By using color channel information, local color content information can be readily accessed and evaluated, and after the exact nature or degree of a red-eye effect is determined from evaluation of the color channel information, the data may be readily corrected by a number of different techniques.

Abstract: A method of noise removal from a digital image, especially moiré noise, comprising providing a three-dimensional representation of a at least one image color channel as a surface over the plane of the image, creating a virtual surface patch, placing the surface patch against topography in the three-dimensional surface mapping of the image so that the virtual surface patch intersects topography of the three-dimensional surface with respect to at least some pixels of the image surface region, adjusting the height, tilt and curvature of the surface patch with respect the image surface in order to optimally represent the surface, then estimating a palliative value for the image surface for at least one pixel within the area of the surface patch from the adjustment of the surface patch, and replacing the value of the at least one pixel in the at least one image color channel with the palliative value.

Abstract: A method of correcting image saturation is performed by defining saturated colors in a chromaticity color space; and deriving an overall correction of the saturation of colors in the image using the defined saturation of these colors in conjunction with a table of corrections indexed by hue and lightness. This process has a unique attribute of being able to automatically decrease saturation in regions of an image where oversaturation is detected.

Abstract: Image defects in a digital image are reduced by a process comprising: providing a digital image data set in the form of a matrix of pixels; selecting a sub-matrix comprising at least a 5×5 matrix of pixels; identifying a pixel within the sub-matrix to be treated as a central pixel; determining a value for at least one optical property in the central pixel; selecting at least four pixels around the central pixel as averaging pixels, at least two of the averaging pixels being in a position in the sub-matrix that is not adjacent the position in the matrix of the central pixel; determining a value for the at least one optical property for the at least four averaging pixels; averaging the values for the at least one optical property for more than one of the at least four averaging pixels to provide an average treatment value for the central pixel; assigning the average treatment value for the central pixel to the central pixel; and storing the average treatment value assigned to the central pixel.

Abstract: A method of automatic contrast correction comprises providing digital image data, representing the data in the form of a brightness histogram, determining a measure of central tendency for said histogram, adding a shift value to the measure of central tendency to provide an adjusted measure of central tendency, using the both the determined and adjusted measures of central tendency to determine the exponent of a tone reproduction curve, and applying the tone reproduction curve to the brightness values of the image. Additionally, the method may provide further correction by applying to the brightness values of the image an S-shaped tone reproduction curve that does not change a measure of central tendency of the brightness histogram.