Computer graphics processing and selective visual display system – Display driving control circuitry – Adjusting display pixel size or pixels per given area
Reexamination Certificate
2000-12-12
2003-08-19
Shalwala, Bipin (Department: 2673)
Computer graphics processing and selective visual display system
Display driving control circuitry
Adjusting display pixel size or pixels per given area
C345S611000, C382S275000
Reexamination Certificate
active
06608632
ABSTRACT:
THE FIELD OF THE INVENTION
Embodiments of the present invention relate to the field of displaying high resolution images on displays with lower resolution, where the displays use a triad arrangement to display the R, G, and B or other components of the image. This triad arrangement is common in direct view LCD displays, for example, and in such an arrangement, a single pixel is composed of 3 side-by-side subpixels. Each subpixel controls only one of the three primaries (i.e., R, G and B) and is, in turn, usually controlled solely by the primaries of the digital image representation. The high-resolution image may be available in memory, or may be available directly from an algorithm (vector graphics, some font designs, and computer graphics).
BACKGROUND
The most commonly used method for displaying high-resolution images on a lower resolution display is to sample the pixels
2
of the high-resolution image
4
down to the resolution of the low-resolution display
6
, as shown in FIG.
1
. Then, the R, G, B values of each downsampled color pixel
8
are mapped to the separate R, G, B elements
10
,
12
and
14
of each display pixel
16
. These R, G, B elements
10
,
12
and
14
of a display pixel are also referred to as subpixels. Because the display device does not allow overlapping color elements, the subpixels can only take on one of the three R, G, or B colors, however, the color's amplitude can be varied throughout the entire greyscale range (e.g., 0-255). The subpixels usually have a 1:3 aspect ratio (width:height), so that the resulting pixel
16
is square. The subsampling/mapping techniques do not consider the fact that the display's R, G, and B subpixels are spatially displaced; in fact they are assumed to be overlapping in the same manner as they are in the high-resolution image. This type of sampling may be referred to as sub-sampling or traditional sub-sampling.
The pixels of the high-resolution image
4
are shown as three slightly offset stacked squares
8
to indicate their RGB values are associated for the same spatial position (i.e., pixel). One display pixel
16
, consisting of one each of the R, G and B subpixels
10
,
12
and
14
is shown as part of the lower-resolution triad display
6
in
FIG. 1
using dark lines. Other display pixels are shown with lighter gray lines.
In this example, the high-resolution image has 3× more resolution than the display (in both horizontal and vertical dimensions). Since this direct subsampling technique causes aliasing artifacts, various methods are used, such as averaging the neighboring unsampled pixels in with the sampled pixel. Note that the common technique of averaging neighboring elements while subsampling is mathematically equal to prefiltering the high resolution image with a rectangular (rect) filter. Also, note that techniques of selecting a different pixel than the leftmost (as shown in this figure) can be considered as a prefiltering that affects only phase. Thus, most of the processing associated with preventing aliasing can be viewed as a filtering operation on the high-resolution image, even if the kernel is applied only at the sampled pixel positions.
An achromatic image, as defined in this specification and claims has no visible color variation. This achromatic condition can occur when an image contains only one layer or color channel, or when an image has multiple layers or color channels, but each color layer is identical thereby yielding a single color image.
It has been realized that the aforementioned technique does not take advantage of potential display resolution. Background information in this area may be accessed by reference to R. Fiegenblatt (1989), “Full color imaging on amplitude color mosaic displays” Proc. SPIE V. 1075, 199-205; and J. Kranz and L. Silverstein (1990) “Color matrix display image quality: The effects of luminance and spatial sampling”, SID Symp. Digest 29-32 which are hereby incorporated herein by reference.
For example, in the display shown in
FIG. 1
, while the display pixel
16
resolution is ⅓ that of the high resolution image (source image)
4
, the subpixels
10
,
12
and
14
are at a resolution equal to that of the source (in the horizontal dimension). If this display were solely to be used by colorblind individuals, it would be possible to take advantage of the spatial positions of the subpixels. This approach is shown in
FIG. 2
below, where the R, G, and B subpixels
10
,
12
and
14
of the display are taken from the corresponding colors of different pixels
11
,
13
and
15
of the high-resolution image. This allows the horizontal resolution to be at the subpixel resolution, which is 3× that of the display pixel resolution.
But what about the viewer of the display who is not color-blind? That is, the majority of viewers. Fortunately for display engineers, even observers with perfect color vision are color blind at the highest spatial frequencies. This is indicated below in
FIG. 3
, where idealized spatial frequency responses of the human visual system are shown.
Here, luminance
17
refers to the achromatic contact of the viewed image, and chrominance
19
refers to the color content, which is processed by the visual system as isoluminant modulations from red to green, and from blue to yellow. The color difference signals R-Y and B-Y of video are rough approximations to these modulations. For most observers, the bandwidth of the chromatic frequency response is ½ that of the luminance frequency response. Sometimes, the bandwidth of the blue-yellow modulation response is even less, down to about ⅓ of the luminance. Sampling which comprises mapping of color elements from different image pixels to the subpixels of a display pixel triad may be referred to as sub-pixel sampling.
With reference to
FIG. 4
, in the horizontal direction of the display, there is a range of frequencies that lie between the Nyquist of the display pixel
16
(display pixel=triad pixel, giving a triad Nyquist at 0.5 cycles per triad pixel) and the Nyquist frequency of the sub-pixels pixels elements
10
,
12
and
14
(0.5 cycles per subpixel=1.5 cycles/triad pixels). This region is shown as the rectangular region
20
in FIG.
4
. The resulting sinc functions from convolving the high resolution image with a rect function whose width is equal to the display sample spacing is shown as a light dashed-dot curve
22
. This is the most common approach taken for modeling the display MTF (modulation transfer function) when the display is an LCD.
The sinc function resulting from convolving the high-res source image with a rect equal to the subpixel spacing is shown as a dashed curve
24
, which has higher bandwidth. This is the limit imposed by the display considering that the subpixels are rect in
1
D. In the shown rectangular region
20
, the subpixels can display luminance information, but not chromatic information. In fact, any chromatic information in this region is aliased. Thus, in this region, by allowing chromatic aliasing, we can achieve higher frequency luminance information than allowed by the triad (i.e., display) pixels. This is the “advantage” region afforded by using sub-pixel sampling.
For applications with font display, the black & white fonts are typically preprocessed, as shown in FIG.
5
. The standard pre-processing includes hinting, which refers to the centering of the font strokes on the center of the pixel, i.e., a font-stroke specific phase shift. This is usually followed by low-pass filtering, also referred to as greyscale antialiasing.
The visual frequency responses (CSFs) shown in
FIG. 3
are idealized. In practice, they have a finite falloff slope, as shown in FIG.
6
A. The luminance CSF
30
has been mapped from units of cy/deg to the display pixel domain (assuming a viewing distance of 1280 pixels). It is shown as the solid line
30
that has a maximum frequency near 1.5 cy/pixel (display pixel), and is bandpass in shape with a peak near 0.2 cy/pixel triad. The R:G CSF
32
is shown as the das
Daly Scott J.
Kovvuri Rajesh Reddy K.
Krieger Scott C.
Osorio Ricardo
Rabdau Matthew D.
Ripma David C.
Shalwala Bipin
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