Microsoft Technology Licensing, LLC

Andrew C Godfrey

J Andrew Goossen

Hock San Lee

Ikko Fushiki

Michael David Marr

Michael Dean Stokes

Gary Keith Starkweather

Gilman Kuey Wong

James Frederick Blinn

Adrian Secchia

The present invention provides a method, apparatus and computer-readable medium for providing high quality substantially visually error-free conversion of color images. The method maps the color values to an expanded colorspace to represent substantially all colors without perceptible visual error and labels an image determined by the mapped color values as an expanded colorspace image. Thus, the present invention may be utilized to provide a linear color management system. In a 16 bit color data value system, transparency/opaqueness information may be stored, and premultiplied or premultiplied and normalized values may be used for blending.

Visually error-free color image representation

An optimal filter kernel, formed by convolving a box filter with a filter of fixed integer width and unity area, is used to perform image resizing and reconstruction. The optimal filter has forced zeros at locations along a frequency scale corresponding to the reciprocal of the spacing of one or more pixels that comprise a source image to be resized. When a rescale value for a source image is selected, the optimal filter kernel is computed, mapped to the source image, and centered upon a location within the source image corresponding to the position of an output pixel to be generated. The number of pixels that lie underneath the optimal filter kernel is established by multiplying the number of pixels that comprise the width of the source image by the selected rescale value. Upon mapping the optimal filter kernel, the output pixel values that comprise the resized image are then evaluated by processing the one or more source image pixels, such as through interpolation. Alternatively, the output pixel values of the resized image are calculated by performing partial integral analysis with respect to a standard filter kernel of fixed width and unity area. The output pixel values are calculated by multiplying the pixel value for each pixel under the kernel by the area of the standard filter kernel surrounding the pixel. The products are then summed to reveal the output pixel value, and placed into the output image buffer. Both of these methods speed up the computation process, while producing a ripple free output image.

Generating resized images using ripple free image filtering

A system and method for processing color objects provides optimal processing quality by supporting both a perceptual-based color space and a physical-based color space and utilizing both color spaces for color processing in an integrated manner transparent to the end user. The graphics engine of the system includes a module for converting a color object being processed between the perceptual-base color space and the physical-based color space. During color processing that may involve various perceptual-based and physical-based operations, the graphics engine automatically converts the color object from one of the perceptual-based and physical-based color spaces to the other depending on the color processing operation to be performed. The graphics engine may also perform conversions on input graphic data from an input device to one of the dual color spaces for processing and converting a processed class object into the color space of an output device for displaying or printing.

System and method for processing color objects in integrated dual color spaces

Improving a process in which information is read, modified, and written, and in which reading information is more costly (e.g., slower) than writing information. The information may be pixel information from a second (or remote) image and the modification may be a blending operation with a first (or local) image. The pixel information of the second (or remote) image may be stored in a video display frame buffer at a display adapter. The display adapter may be coupled via a bus, such as a PCI bus for example, with a CPU (or other machine) which performs the modification, such as image blending for example. This process is improved by limiting the number of reads of the pixel information of the second (or remote) image. Further, reads may be combined when doing so improves read performance and when alignment conditions are met. All modify and all or some write steps may be performed after all read steps have been performed, rather than performing all three (3) steps on a pixel-by-pixel, or pixel vector-by-pixel vector basis.

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Redmond, WA, United States of America

Andrew C Godfrey