Computer graphics processing and selective visual display system – Computer graphics processing – Attributes
Reexamination Certificate
1999-03-31
2002-01-08
Luu, Matthew (Department: 2672)
Computer graphics processing and selective visual display system
Computer graphics processing
Attributes
C345S589000
Reexamination Certificate
active
06337692
ABSTRACT:
TECHNICAL FIELD
The present invention relates generally to image processing, and more particularly relates to a system and methods that allow the user of an image processing system to implement scene-by-scene color manipulation in the primary color domain to color correction regions of a video image isolated in the hue domain using hue, saturation, and luminance qualification.
BACKGROUND OF THE INVENTION
In a video signal color correction system, various types of image processing are often employed to create, enhance, compress, filter, or otherwise modify characteristics of the video image. In certain types of video image processing systems, especially post-production color correction systems for motion picture film and/or video tape, color corrections are typically made on a scene-by-scene basis. A “scene” is a sequential collection of images, often shot from the same camera, having the same viewpoint, composed in a certain way, etc. An operator using a typical post-production color correction system observes a target frame of the scene on a video monitor, adjusts the color and other parameters of the frame until it is aesthetically satisfactory, and stores the color correction parameters in system memory. The color correction system preferably automates the application of the stored color correction parameters to the other frames of the scene.
For example, the system operator or “colorist” typically selects a scene to manipulate, and then selects a particular frame from the scene for manual manipulation. The colorist views the target frame as a still image on the system monitor and applies color corrections via a control panel to adjust the color parameters for a particular region of the target frame. The color correction system typically allows the colorist to isolate a particular region of the frame and to alter the intensity of the primary color components, red, green and blue, which in various combinations produce all of the colors that the system can produce. The colorist may than apply color corrections to another region of the frame, and so forth, until all of the desired regions have been color corrected. The correction settings are then stored in system memory.
After the colorist is satisfied with the adjustments made to the target frame, the color correction system, which is typically computer-controlled, automatically applies the stored color corrections to each frame in the scene on a frame-by-frame basis. The color corrected frames of the scene are then recorded on film or videotape. The steps are repeated for other scenes in the film or video tape, often with different correction settings stored for different scenes. This process may be repeated as needed to create a color corrected master film or video tape that reflects multiple color adjustments to multiple frames in multiple scenes. In the general case, multiple color adjustments may be applied to all of the frames of a motion picture or other video program.
Devices are known in the art for isolating a region of a still image for applying one set of color corrections, with other regions of the image receiving a different set of color corrections. These devices allow a color correction system to isolate a particular region of a frame to receive special image processing. For example, when color correcting a soft drink commercial it may be desirable to isolate the beverage container from the remainder of the image. The color of the beverage container may then be enhanced to make the can stand out from the rest of the image. But applying color correction to each frame of a film or video tape individually is extremely tedious and time consuming. Automating the process of applying the color correction parameters defined for one frame of a scene to the other frames is, therefore, highly desirable.
Automatically isolating a color correction region presents a difficult technical problem because the region of interest may change in size, shape, location, and/or geometry over the frames in a scene. That is, an object in a video scene typically moves over the frames of the scene. For example, consider a scene in which a bottle is lifted, tilted, moved toward a glass, turned toward the viewer, and then further tilted to pour the contents of the bottle into a glass. In this scene, the geometry of the bottle changes from a side view of the bottle (an irregular shape) to a top view of the bottle (an essentially round shape). The bottle also changes in location and size over the several frames of the scene.
The state of the art in automated color correction technology is somewhat lacking for a number of reasons. Video images are typically defined on a pixel-by-pixel basis by intensity levels of the primary colors, red, green and blue (R,G,B). In a typical color correction system, the primary colors are mixed in varying intensities to produce all of the colors that the system can produce. Color data in the R,G,B format, often referred to as the “primary color domain,” may be linearly transformed into secondary color components, hue, saturation and luminance, which is sometimes referred to as the “hue domain.” Certain prior art color correction systems apply color corrections in the primary color domain, whereas others apply color corrections in hue domain.
Operating in the primary color domain has certain drawbacks associated with isolating color correction regions. In a color video image, the intensity of the red, green, and blue components for a particular object depicted in a scene can vary from frame to frame in response to the brightness, or shadowing, of the item. In addition, many different colors may have the same intensity of one of the particular color components. For this reason, it is difficult to isolate a particular object in a scene by focusing on the intensity of the red, green, and blue constituents of the pixels of the object. In other words, isolating a particular object, as that object moves from frame to frame within a scene, is difficult when analyzing the video data in the primary color domain.
Color correction systems that operate in the hue domain have been developed to overcome the region isolation drawbacks associated with color correction systems that operate in the primary color domain. For example, color correction systems have been developed that allow an operator to select and manipulate a color correction region in the hue domain. These systems typically include equipment for generating and positioning a cursor on a video monitor to allow selection of a color correction region defined by the hue at the selected position. Circuitry responsive to the cursor location selects one of a plurality of color correction circuits to become operative for directing secondary color correction parameters (i.e., adjustments to the hue, saturation, and luminance) only to regions in the video image corresponding to the hue selected by the cursor. This type of system therefore allows application of secondary color correction parameters to all regions of the image bearing the hue that was selected with the cursor.
Color correction systems that operate in the hue domain, however, also exhibit certain drawbacks. First, they incur a relatively high processing overhead because the entire video image is typically transformed from the primary color domain to the hue domain. Color corrections are then applied in the hue domain, and the image is then transformed back from the hue domain to the primary color domain. Thus, the system performs two linear transformations on the entire video image even though no color corrections may be applied to large portions of the image. As a result, even those portions of the video image that are not color corrected must be transformed from the primary color domain to the hue domain, and then back to the primary color domain.
Second, transforming color data from the primary color domain to the hue domain, and then back to the primary color domain, can impart “color artifacts” into the video image. That is, applying a linear mathematical operation to digital data, followed by the inver
Barton Nicholas
Gu Xueming Henry
Rai Sanjay Devappa
Taylor Troy
Da Vinci Systems, Inc.
Good-Johnson Motilewa
Luu Matthew
Morris Manning & Martin LLP
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