Abstract: Properties of pixels of a digital image are sampled within different subdivisions of an editing tool impression to produce different pixel property distributions. The property distributions from each region may be automatically classified to identify different edit classes within the property space, which are then used to apply an edit effect to the digital image within the tool impression. The edit classes are represented by an edit profile, the generation of which may be completely automated based on selection of a tool impression, or partially automated using the selection of the tool impression and receipt of classification guidance input, such as one or more parameters received from user input or a configuration file. The edit classes may also be generated without reference to the pixel property distributions, such as via user input.

Abstract: Properties of pixels of a digital image are sampled within different subdivisions of an editing tool impression to produce different pixel property distributions. The property distributions from each region may be automatically classified to identify different edit classes within the property space, which are then used to apply an edit effect to the digital image within the tool impression. The edit classes are represented by an edit profile, the generation of which may be completely automated based on selection of a tool impression, or partially automated using the selection of the tool impression and receipt of classification guidance input, such as one or more parameters received from user input or a configuration file. The edit classes may also be generated without reference to the pixel property distributions, such as via user input.

Abstract: Properties of pixels of a digital image are sampled within different subdivisions of an editing tool impression to produce different pixel property distributions. The property distributions from each region may be automatically classified to identify different edit classes within the property space, which are then used to apply an edit effect to the digital image within the tool impression. The edit classes are represented by an edit profile, the generation of which may be completely automated based on selection of a tool impression, or partially automated using the selection of the tool impression and receipt of classification guidance input, such as one or more parameters received from user input or a configuration file. The edit classes may also be generated without reference to the pixel property distributions, such as via user input.

Abstract: Properties of pixels of a digital image are sampled within different subdivisions of an editing tool impression to produce different pixel property distributions. The property distributions from each region may be automatically classified to identify different edit classes within the property space, which are then used to apply an edit effect to the digital image within the tool impression. The edit classes are represented by an edit profile, the generation of which may be completely automated based on selection of a tool impression, or partially automated using the selection of the tool impression and receipt of classification guidance input, such as one or more parameters received from user input or a configuration file. The edit classes may also be generated without reference to the pixel property distributions, such as via user input.

Abstract: Properties of pixels of a digital image are sampled within different subdivisions of an editing tool impression to produce different property distributions. The subdivisions may be differently-located within the tool impression. The property distributions from each region are classified to identify different edit classes within the property space, which are then used to apply an edit effect to the digital image within the tool impression. The edit classes may be represented by an edit profile in two or more dimensions (e.g., applying to one or more pixel properties).

Abstract: Properties of pixels of a digital image are sampled within different subdivisions of an editing tool impression to produce different pixel property distributions. The property distributions from each region may be automatically classified to identify different edit classes within the property space, which are then used to apply an edit effect to the digital image within the tool impression. The edit classes are represented by an edit profile, the generation of which may be completely automated based on selection of a tool impression, or partially automated using the selection of the tool impression and receipt of classification guidance input, such as one or more parameters received from user input or a configuration file. The edit classes may also be generated without reference to the pixel property distributions, such as via user input.

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: A color correction device for correcting colors in a color image comprises: coordinates for registering points in a first color space of at least one standard point, the first color space having axes for specifying colors; a second set of coordinates for registering points in a second color space of at least one standard point, the second color space having coordinates that include at least one coordinate for specifying color hue; a translator to convert image data of at least one point in the first color space to coordinates in the second color space; a modifier for modifying at least hue within image data in the second color space to form corrected image data in the second color space; and a translator for transferring corrected image data in the second color space to corrected image data in the first color space.

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: 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: 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 color correction device for correcting colors in a color image comprises: