Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
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COLOR FILTER PATTERNS FOR IMAGE SENSORS
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates to color image sensors that converts optical
illumination
into electrical signal arrays. More particularly, this invention is related to
a new color
filter pattern for an image sensor to improve color image sensing sensitivity
and total
image quality when perceived from human eyes by adjusting signal to noise
ratio of
different colors.
2. Description of the Related Art
Conventional technologies of designing and manufacturing color image sensors
are still confronted with several technical difficulties and limitations. More
specifically,
color image sensors implemented with current technologies are still hindered
by low
level of sensing sensitivities, limited spatial resolutions and problems
associated with
color aliasing. Generally, an image sensor is applied for sensW g either black
and white or
color images. The invention of this Application is related to color image
sensors. There
are several different technologies implemented for the color image sensors to
generate
color images from a single array of sensing elements. The most commonly used
method
in a color image sensor is to coat on the surface of a sensing array with a
special pattern
of different color filters. Conventional color image sensors apply two kinds
of color filter
patterns. Fig. 1 shows the first color filter pattern, i.e., the CYeMgG
Pattern (or
complementary color filter pattern), comprising C (Cyan), Ye (Yellow), Mg
(Magenta), G
(Green) pattern. Figs. 2 and 3 show another kind of color filter patterns that
utilize
primary color filters, comprising R (Red), G (Green), and B (Blue), arranged
in either a
Bayer Pattern shown in Figure 2 or a Hexagonal RGB Pattern as that shown in
Fig. 3.
In a color image sensor implemented with the CYeMgG Pattern, the sensing
element array is formed by a plurality of macro pixels, with each macro pixel
consisting
of 4 {elementary) pixels. Each pixel is coated with a single color, either C,
or Ye, or Mg, or
G. However, since the display industry commonly uses the primary color
pattern, i.e.,
RGB (red, green, blue) colors, instead of a CYeMgG pattern, therefore,
conversion of a
CYeMgG color pattern into a RGB color pattern is carried out by performing the
color
3
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matrix operations. Furthermore, since each pixel contains only one color
(either C, or Ye,
or Mg, or G), in order to obtain other (R, G, and B) colors for the same
pixel, interpolation
methods are used to generate the missing colors from neighboring pixels. For
an image
sensor implemented with a Bayer Pattern (US Patent#3,971,065), the sensing
element
array is also formed by a plurality of macro pixels, with each macro pixel
consisting of
four pixels coated with either R, or G, or B color filter. A Bayer Pattern
further requires
that among each macro pixel, two pixels in either diagonal direction must be
coated with
G or LumW ance and the other two pixels :must be coated ~Nith B and R or two
other
colors sensitive to DIFFERENT spE3ctral regions. Again since each pixel
contains only one
color (either R, or G, or B), in order to obtain oilier (two) colors for the
same pixel,
interpolation methods are used to generate the missing colors from neighboring
pixels.
Bayer pattern has four different geometric structures, with R, G, B located in
different
locations in the four pixels. Referring to Fig. 3 again for the Hexagonal RGB
Pattern, a
macro pixel contains only three sensing pixels of R, G, and B wherein each
element is
tessellated in hexagonal fashion. The R, G, B colors are equally and evenly
placed in the
sensing array. Interchanging the positions of two colors still form a
Hexagonal RGB
Pattern.
As discussed above, the color filter technologies that implement either the
CYeMgG Pattern, Bayer Pattern, or Hexagonal RGB Pattern have at least three
common
technical difficulties. A first difficulty is the reduction of sensing
sensitivities caused by
the use of multiple layers of filters when compared to black and white
sensors. 'The
second difficulty is the reduction of effective spatial resolution due to the
need of color
interpolation. The requirement of color interpolation also introduces the
third difficulty
of color abasing, which can be solved, typically, by low pass filtering, that
however leads
to reduction in image sharpness.
In order to improve the overall sensing sensitivity, U~ Patent 6,137,100
discloses ~
method by balancing the responses from sensing the three primary colors R, G,
and B by
taking into consideration of the fact that the color sensitivities of the
photodiodes are
different, specifically, the photodiodes are most sensitive to green then to
red and lastly
least sensitive to blue. TTie Patented method thus provides largest sensing
area to blue
pixels, and the second largest sensing area to red pixels, and the least
sensing area to
green pixels. However, the improvements in color sensing sensitivity achieved
by this
technique are still quite limited and also the methods are only applicable to
the image
sensor implemented with the color filters of RGB color patterns.
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In order to avoid a requirement of color interpolations, a new calor image
sensor
produced by Foveon is implemented with a three-Layer image sensor as that
shown in
Fig.4. This three-layer color sensor, designated by a model number as "X3
image sensor",
contains three layers of sensing array, with each layer sensing R, G, or B
light spectxum
respectively. The X3 image sensor is able to resolve the difficulties caused
by color
interpolation, but generates new problems due to the difference of the sensing
sensitivities between different layers. The sensing sensitivity of a Lower
layer is smaller
than that of the top layer. Therefore, the overall effective sensing
sensitivity is further
reduced. Additionally, the production yields are degraded as three layers of
sensor are
manufactured and assembled by using more complicate and time consuming
manufacturing processes. Furthermore, there are three times of data to be
processed and
that places additional demand on data transfer and data processing rates and
causes a
significant increase of the production costs of the entire system implemented
with this
X3 image sensor.
Therefore, a need still exists to provide new and improved tecluliques and
methods for designing and manufacturing a color image sensor to resolve these
technical difficulties.
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SUMMARY OF THE PRESENT INVENTION
An object of this W vention is to provide a new color filter pattern for color
image
sensors. The image sensor implemented with this new color filter pattern
provides an
improved color image sensing sensitivity and image sharpness compared with the
traditional CYeMgG pattern, Bayer pattern, or hexagonal pattern. Therefore,
the
limitations and difficulties as those encountered in the prior art are
resolved.
In a first aspect of the invention, the color filter patterns contain three
colors, and
one of these three colors is the luminance of the whole interested spectrum
(e.g., the
white color in the visible light spectrum) commonly designated as Y. This
color is
designated as the leading color. The color filter for luminance is realized by
either a
transparent coating or by applying no coating at all to the filter.
In a second aspect of the invention, besides the luminance filter, the image
sensor
includes tcnTo other color filters that can be of any two complementary colors
or two
primary colors, designated as secondary colors and labeled as S and Q for ease
of
description in this Application. For example, S can be Yellowr, and Q can be
Cyan, or S
can be Red and Q be Blue. The color filter for a particular color, e.g.,
Yellow, is realized
by a coating material or pigments that pass tight spectrum corresponding to
that
particular color, e.g., Yellow.
In a third aspect of the invention, irrespective of which form of tessellation
is used,
the leading color Y must be coated on at least the same number of pixels than
each of the
secondary colors S and Q while S is coated on about the same number of pixels
as Q. The
new color filter pattern may be applied in many different forms of
tessellation including,
but not restricted to, the conventional Bayer Pattern tessellation as that
shown in Fig. 5,
hexagonal tessellation as that shown in Fig. 7, or the YUV422 tessellation as
that shown
in Fig. 9.
In a fourth aspect of the invention, the sensing areas of the pixels or
surface areas
of the micro lenses on the pixels are designed such that the three kinds of
sensing
elements for Y, S, and Q colors have the desired signal to noise ratios (SNR)
for the
lighting condition of particular applications implemented with the image
sensor of this
invention.
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Briefly in a preferred embodiment this invention discloses a method: for
generating a
color filter pattern for a macro pixel of foul elementary pixels. The color
filter pattern
includes a luminance color Y and two other colors S and Q organized in ordered
tessellation. The tessellation includes Bayer tessellation and YUV422
tessellation. The
YUV422 tessellation is widely used as YUV422 format in TV industry where YUV
data
are organized ii1 YUYV interleave format. The method includes a step of
coating the
color filter pattern on top of a macro pixel with color Y on two elementary
sensing pixel
elements, and S and Q each on top of one elementary sensing pixel element. The
method
further includes a step of replicating the macro pixel with the said color
filter pattern in
tile tessellation horizontally and vertically so to obtain an image sensor
array.
These and other objects and advantages of the present invention will no doubt
come obvious to those of ordinary skill in the art after having read the
following
detailed description of the preferred embodiments, which are illustrated in
the various
drawing figures.
BRIEF DESCRIPTION OF THE DRAWINGS
Figure 1 is a diagram of a CYeMgG color filter pattern;
Figures 2 is a diagram of RGB Bayer color filter pattern and the variants;
Figure 3 is a diagram of the Hexagonal RGB color filter pattern;
Figure 4 is a diagram for showing the three-layer color filter technique
implemented by Foveon, Inc. in a X3 image sensor;
Figure 5 is a diagram fox illustrating the YSQ color filter pattern according
to a
Bayer Tessellation and its variants according to the present invention;
Figure 6 shows a preferred embodiment implemented with YYeC color filters of
this invention arranged according to a Bayer tessellations;
Figure ~ is a diagram for illustrating an alternated preferred embodiment of
this
invention implemented with YSQ color filters arranged according to a
'Hexagonal
Tessellation;
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Fig. 8 is a diagram for illustrating an alternated preferred embodiment of
this
invention implemented with YYeC color filters arranged according to a
Hexagonal
Tessellation;
Figure 9 is a diagram of the newly invented YSQ color filter in different
forms of
YUV422 Tessellation;
Figure 10 is a diagram for illustrating an alternated preferred embodiment of
this
invention implemented with YBR color filters arranged according to different
forms of
YUV422 Tessellation;
Figures 11.A and 11 B show cross sectional views of image sensors implemented
with micro-lenses wherein the SNRs of different color pixels are adjusted to W
a desired
values by applying a micro-lens based SNR adjustment method through size and
curvature variations of micro-lenses to change effective sensing areas;
Figure 12 is an area diagram fc7r illustrating an area-based SNR adjustment
method to adjust the SNRs of different color pixels to the desired values.
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DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
Referring to Figs. 5A to 5D for four different color filter patterns
respectively
wherein each pattern includes a plurality of luminance filters designated as Y
and two
other color filters designated as S and Q. The Y color filters for sensing
luminance, i.e.,
white light, are leading color filters and the S and Q filters are secondary
color filters.
The secondary color filters S and Q can be implemented with two complementary
color
filters or two primary color filters. Compared to the number of pixels coated
with S and
Q color filters, luminance color filters as shown are coated on number of
pixels equal to
or more than that coated on either the S or Q color filters. The number of
pixels coated
with S color filters is about the same as the number of pixels that coated
with Q color
filters.
Referring to Fig. 6A to 6D, two secondary colors S and Q are chosen to be
Yellow
(Ye) alld CG'an (C)respectively and Y, S, and Q are organized in a Bayer
pattern. With
this preferred embodiment, the color filter pattern differs from the
conventional Bayer
pattern only in that Green color filter is replaced by White color filter, Red
by Yello~~,
and Blue by Clan. Compared to the conventional Bayer pattern, the color sensor
as
shown in Fig. 6 requires significant changes to generate color images. The
changes are
required because the sensed three colors Y, S and Q, e.g., Y, Ye, and C, do
not form a
color space and they have never been used together in image sensors. For this
reason,
the color filter patterns as shown in Figs. 5 and b require the internal color
processing
circuits to change correspondingly. Additionally, different color
interpolation methods
and matrix operations are needed to recover R, G, B colors from Bayer
patterned now
sensed as Y, S, Q, e.g., Y, Ye, C colors.
This seemingly simple change to the color filter patterns as shown in Figs. 5
and 6,
provides great advantages. First of all, the white color Y has much higher
sensitivity
than green color, and yellow and cyan have much higher sensitivity than red
and blue
respectively. The color image sensor configured according to tile color filter
pattern as
shown can achieve much improved sensing sensitivity. Especially, SiIlCe human
eyes are
more sensitive to luminance than chrominance and since there are more
luminance
components than other color components, for a human viewer the image sharpness
is
increased. Second, both yellow and cyan are complementary colors and therefore
do not
represent chrominance colors (B and R) directly. As a consequency, the
chrominance
components need to be indirectly derived from color interpolation.
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Figs. 7 and 8 show a second set of preferred embodiment where the YSQ patterns
are implemented in Fig. 7 according to a hexagonal tessellation. In Fig. 8,
the YSQ color
filter pattern is again arranged according to a hexagonal tessellation with S
chosen as
Yellow and Q chosen as Cyan. In this tessellation, Y, Ye, and C have about the
same
number of pixels. Meanwhile, in order to achieve better signal to noise ratios
as will be
discussed below, the sensing areas may be configured differently by pr oviding
either
different filter areas or using micro lenses of different curvatures.
Figs. 9 and 10 show a third set of preferred embodiment where the YSQ patterns
are implemented in Fig. 9 according to a YUV422 tessellation. In Fig. 10, the
YSQ color
filter pattern is again arranged according to a YUV422 tessellation with S
chosen as R
and Q chosen as B. In this embodiment, the Y, B, and R colors are used for
coating the
pixels and these pixels are arranged in horizontally interleaved tessellation
including
either Y ( B ~ Y / R, Y ~ R ~ Y ( B, B ( Y ~ R ~ Y, or R ~ Y ~ B ~ Y. Compared
with the
horizontal resolution, the vertical resolution is twice as higher for Y, and
four times
higher for B and R. In order to have a more balanced resolution, different
methods are
implemented. As a first exemplary implementation, the combined width of a
macro
pixel Y ~ B ( Y ~ R, is arranged as twice as the height of a Y pixel. In a
second exemplary
implementation, instead of four pixels, two (R, G, B) pixels are produced
through
interpolation from each macro pixel Y ~ B ~ Y ~ R. Because of the similarity
with the
YUV422 format widely used iti the TV industry, this preferred embodiment is
particularly useful for video sensors. Even this embodiment has similar
tessellations as
that shown in US Patent 6,346,969, the invention as disclosed in this
Application has
superior image quality because of the improved effective sensing sensitivity
by utilizing
an improved Y-S-Q color filters instead of the conventional RGB color filters
when
compared with US Patent 6,346,969.
In all three different tessellations, as those shown in Figs. 5 to 10, there
are more or
about same Y pixels when compared to S and Q pixels. Meanwhile, the S and Q
pixels
have about the same numbers of pixels.
The color image sensor has broad applications. For example, a digital camera
can
achieve immediate image quality improvement by utilizing a color image sensor
as
disclosed in this invention. Typically, a digital camera can easily achieve
acceptable
signal to noise ratio for an outdoor situation. However, in a low light
condition such as
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the requirements for taking an indoor picture, conventional color image
sensors often
experience difficulties to provide sufficient image sensing sensitivity. In a
low light
environment, the SNR for a sensing element highly depends on the color coating
and
semiconductor processing technology of the sensing element {e.g., a photo
diode).
Normally, luminance Y has the highest SNR among all colors. Suppose that S has
a
higher SNR than Q. Let SY, Ss, SQ, be the intrinsic SNR of the sensing element
for color Y,
S, and Q respectively. 'The intrinsic SNR of a color is defined as the SNR of
the color at
unit sensing area. Typically the signal to noise ratio can be calculated as:
Ss = SY / a, SQ = SY / b, (b >= a > 1.0).
If the desired SNRs for Y, S, and Q are DY, Ds, D~ respectively with
Ds = DY / c, DQ = DY / d,
Then sensing areas or the surface areas of the micro lenses for the Y, S, and
Q pixels are
chosen such that a S pixel collects a/c times more photons than a Y pixel, and
a Q pixel
collects b/ d times more photons than a Y pixel. Furthermore, it is noted
that:
a/c ° ( SY / Ss) / (DY / Ds) _ (SY' Ds) / (Ss 'DY)
b/ d = C SY / sQ) / (DY / DQ) ° (SY ' DQ> / (sQ ' DY>
The difference between sensing areas or surface areas of the micro lenses
between
a color pair S and Y, or Q and Y, is determined by both the desired and
intrinsic SNRs of
S and Y, or those of Q and Y. As shown in Fig. 11, the desired SNRs are
achieved by
adjusting surface areas or curvatures of the micro lenses for different
colors. These
drawings are exemplary and are not intended to limit the scope of this
invention. The
method of using the micro lenses for sensing areas adjustment can be either
used
independently or together with the sensing area adjustment method described
below.
Fig. 12 shows a method that achieves desired SNRs by adjusting sensing areas
of
different color pixels. Compared to the disclosure made in US Patent
6,137,100, the SNR
balancing techniques are different. The balancing techniques as disclosed by
US Patent
6,137,100 is only applied to the conventional R-G-B color space and the Bayer
tessellation,
while the balance of this invention is applied to the Y-S-Q color space for
all different
kinds of tessellations. Furthermore, the SNR balancing method of this
invention is not
to equalize the color light photons received for R, G, and B pixels
respectively, but to
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achieve the desired SNRs for Y, S, and Q respectively. The technique of this
invention
can produce better image quality for human eyes. The better image qualities
are
achieved because the human eyes are more sensitive to luminance than to
cllrominance.
For this reason, the desired SNR for Y is higher than the desired SNRs for S
and Q.
Instead of adjusting even intensity of the R-G-B colors, a more sensible
adjustment is to
adjust the SNRs for better viewing as that most suitable for human eyes when
looking
from a human perspective. Other than the changes of planar sensing areas as
shown in
Fig. 12, additional sensing area adjustment can be achieved by using micro
lenses on
different color filters as that shown in Fig. 11 with micro lenses of
different sizes and
curvatures. The SNRs can therefore be flexibly adjusted to achieve best image
quality by
combining planar sensing area var rations together with micro lens
adjustments.
In summary, this invention discloses an improved color image sensor
implemented with
a color filter pattern that has a leading color, the luminance (or white color
as in the
visible light spectrum) Y of the whale interested spectrum, and two other
secondary
colors S and Q each corresponding one segment of the interested spectrum. The
secondary colors S and Q can be chosen from any two of the primary colors R,
G, and B,
or from any complementary color pairs out of C, Ye, Mg, and G, or from two
other
specifically desired colors (e.g., an infrared color and an ultraviolet color)
for special
applications. The leading color is applied to about the same or more number of
pixels
than each of the secondary colors. The color filter pattern can have any form
of
tessellation, including, but not restricted to, Bayer pattern tessellation,
hexagonal
tessellation, or YUV422 tessellation. The sensing areas and/or surface areas
or curvature
of the micro lenses of the color pixels are so chosen to achieve desired SNRs
for the color
pixels. This inventions thus uses a different color filter pattern to improve
the sensitivity
and increase image sharpness without the side effects of the X3 method. In
addition, the
method can be used to produce YUV sensors in very simple ways.
Although the present invention has been described in terms of the presently
preferred embodiments, it is to be understood that such disclosure is not to
be
interpreted as limiting. Various alterations and modifications will no doubt
become
apparent to those skilled in the art after reading the above disclosure.
Accordingly, it is
intended that the appended claims be interpreted as covering all alterations
and
modifications as fall within the true spirit and scope of the invention.
