Abstract: A method of matching image color and or luminance characteristics in an image processing system. In order to match an input image with a reference image, a color transformation M is initialised (601). An output image is copied (602) from the input image. The following sequence of operations is then repeated: Output and reference images are displayed on a system monitor. The user identifies (603) a highlight, shadow or overall region in both images. These regions are processed (604) to identify a difference (605). The difference is concatenated (606) onto transformation M. The output image is updated (607) by processing the input with M.

Abstract: A method of modifying image data in which image colors are to be modified, including a first step of initializing a color vector function, in which color vector is a function of luminance, and then the following repeated steps. A user defines a luminance range (616, 617) and a color vector (620) for that range. The color vector function is updated (601) and a look-up table (407) is generated (602) that is addressable by luminance. Image data (405) is processed by calculating each pixel's luminance and using this to address the red, green and blue values in the look-up table (407). The red, green and blue values so obtained are then added to each pixel's original red, green and blue values, resulting in output image pixels.

Abstract: A method of matching image color and or luminance characteristics in an image processing system. In order to match an input image with a reference image, a color transformation M is initialised (601). An output image is copied (602) from the input image. The following sequence of operations is then repeated: Output and reference images are displayed on a system monitor. The user identifies (603) a highlight, shadow or overall region in both images. These regions are processed (604) to identify a difference (605). The difference is concatenated (606) onto transformation M. The output image is updated (607) by processing the input with M.

Abstract: A method of matching image color and or luminance characteristics in an image processing system. In order to match an input image with a reference image, a color transformation M is initialised (601). An output image is copied (602) from the input image. The following sequence of operations is then repeated: Output and reference images are displayed on a system monitor. The user identifies (603) a highlight, shadow or overall region in both images. These regions are processed (604) to identify a difference (605). The difference is concatenated (606) onto transformation M. The output image is updated (607) by processing the input with M.

Abstract: A method of matching image color and or luminance characteristics in an image processing system. In order to match an input image with a reference image, a color transformation M is initialised (601). An output image is copied (602) from the input image. The following sequence of operations is then repeated: Output and reference images are displayed on a system monitor. The user identifies (603) a highlight, shadow or overall region in both images. These regions are processed (604) to identify a difference (605). The difference is concatenated (606) onto transformation M. The output image is updated (607) by processing the input with M.

Abstract: A method of modifying image colors in which a user identifies a source color (707) and a destination color (708) having a common luminance (704). Source and destination color volumes (821, 822) are defined by firstly identifying two points (811, 812) opposite in color to the source (707), and secondly by selecting the most distant of white or black (813) as another point. The source color volume (821) and destination color volume (822) have these three points in common. A transformation is then defined (804) to transform from the source to the destination volume. This transformation, when applied (805) to image colors, results in the color change intended by the user.

Abstract: A method of matching image color and or luminance characteristics in an image processing system. In order to match an input image with a reference image, a color transformation M is initialized (601). An output image is copied (602) from the input image. The following sequence of operations is then repeated: Output and reference images are displayed on a system monitor. The user identifies (603) a highlight, shadow or overall region in both images. These regions are processed (604) to identify a difference (605). The difference is concatenated (606) onto transformation M. The output image is updated (607) by processing the input with M.

Abstract: A process of defining a color volume for use in a process of color keying, in which a foreground image (405) is composited against a background image (407). The foreground image (405) contains regions of a background color (723). The user defines diamond shaped areas (611, 621) in PbPr color dimensions, and luminance ranges (612, 622). Tolerance and softness volumes (613, 623) are defined in this way, and a transformation is defined for each. Foreground pixels are processed (602) to determine a background, foreground, or softness condition for a matte (406). Softness represents a partial mix of foreground and background. The mix level is calculated by re-centering (1201) the softness volume, and processing (1206) with an optional sharpness parameter (706).

Abstract: A method of modifying image data in which image colors are to be modified, including a first step of initialising a color vector function, in which color vector is a function of luminance, and then the following repeated steps. A user defines a luminance range (616, 617) and a color vector (620) for that range. The color vector function is updated (601) and a look-up table (407) is generated (602) that is addressable by luminance. Image data (405) is processed by calculating each pixel's luminance and using this to address the red, green and blue values in the look-up table (407). The red, green and blue values so obtained are then added to each pixel's original red, green and blue values, resulting in output image pixels.

Abstract: A process of defining a color volume for use in a process of color keying, in which a foreground image (405) is composited against a background image (407). The foreground image (405) contains regions of a background color (723). The user defines diamond shaped areas (611, 621) in PbPr color dimensions, and luminance ranges (612, 622). Tolerance and softness volumes (613, 623) are defined in this way, and a transformation is defined for each. Foreground pixels are processed (602) to determine a background, foreground, or softness condition for a matte (406). Softness represents a partial mix of foreground and background. The mix level is calculated by re-centring (1201) the softness volume, and processing (1206) with an optional sharpness parameter (706).

Abstract: A method of modifying image colors in which a user identifies a source color (707) and a destination color (708) having a common luminance (704). Source and destination color volumes (821, 822) are defined by firstly identifying two points (811, 812) opposite in color to the source (707), and secondly by selecting the most distant of white or black (813) as another point. The source color volume (821) and destination color volume (822) have these three points in common. A transformation is then defined (804) to transform from the source to the destination volume. This transformation, when applied (805) to image colors, results in the color change intended by the user.

Abstract: A method of matching image color and or luminance characteristics in an image processing system. In order to match an input image with a reference image, a color transformation M is initialized (601). An output image is copied (602) from the input image. The following sequence of operations is then repeated: Output and reference images are displayed on a system monitor. The user identifies (603) a highlight, shadow or overall region in both images. These regions are processed (604) to identify a difference (605). The difference is concatenated (606) onto transformation M. The output image is updated (607) by processing the input with M.