Abstract: Properties of pixels in a digital image are sampled within different subdivisions of an editing tool impression to produce different property distributions. The different subdivisions can automatically alter their size, geometry, and/or location, based on image content within one or more of the subdivisions, in order to encompass a set of pixels having a substantially uniform distribution of a pixel property. Uniformity can be defined relative to the editing operation or context of the image. 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.

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 in a digital image are sampled within different subdivisions of an editing tool impression to produce different property distributions. The different subdivisions can automatically alter their size, geometry, and/or location, based on image content within one or more of the subdivisions, in order to encompass a set of pixels having a substantially uniform distribution of a pixel property. Uniformity can be defined relative to the editing operation or context of the image. 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.

Abstract: Properties of pixels in a digital image are sampled within different subdivisions of an editing tool impression to produce different property distributions. The different subdivisions can automatically alter their size, geometry, and/or location, based on image content within one or more of the subdivisions, in order to encompass a set of pixels having a substantially uniform distribution of a pixel property. Uniformity can be defined relative to the editing operation or context of the image. 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.

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: Perspective distortion in an imaged scene is corrected by identifying a group of points in the imaged scene such that the group of points define a shape. Two vanishing points are determined based on the group of points in the imaged scene. The process determines a first set of reference points within the shape defined by the group of points and transforms the first set of reference points into a second set of reference points. An aspect ratio associated with the first set of reference points is adjusted and the imaged scene is transformed to reduce perspective distortion in the imaged scene.

Abstract: Properties of pixels in a digital image are sampled within different subdivisions of an editing tool impression to produce different property distributions. The different subdivisions can automatically alter their size, geometry, and/or location, based on image content within one or more of the subdivisions, in order to encompass a set of pixels having a substantially uniform distribution of a pixel property. Uniformity can be defined relative to the editing operation or context of the image. 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.

Abstract: Properties of pixels in a digital image are sampled within different subdivisions of an editing tool impression to produce different property distributions. The different subdivisions can automatically alter their size, geometry, and/or location, based on image content within one or more of the subdivisions, in order to encompass a set of pixels having a substantially uniform distribution of a pixel property. Uniformity can be defined relative to the editing operation or context of the image. 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.

Abstract: Perspective distortion in an imaged scene is corrected by identifying a group of points in the imaged scene such that the group of points define a shape. Two vanishing points are determined based on the group of points in the imaged scene. The process determines a first set of reference points within the shape defined by the group of points and transforms the first set of reference points into a second set of reference points. An aspect ratio associated with the first set of reference points is adjusted and the imaged scene is transformed to reduce perspective distortion in the imaged scene.

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 reducing artifacts in an image previously processed by block transform encoding may comprise the steps of:

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 removing an object from a digital image comprising,

Abstract: A method of processing digital image data comprises

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.