Patent Abstract:
An apparatus and method for performing automatic exposure control based on current measured luminance of an image and dynamic/modifiable target luminance levels. Exposure adjustments and/or adjustments to the dynamic/modifiable target luminance windows are based on the measured luminance and threshold settings to improve image quality while avoiding oscillations and other problems typically associated with automatic exposure.

Full Description:
FIELD OF THE INVENTION 
   The invention relates generally to imaging devices and more particularly to improved automatic exposure control in an imaging device. 
   BACKGROUND 
   CMOS imagers are low cost imaging devices. A fully compatible CMOS sensor technology enabling a higher level of integration of an image array with associated processing circuits would be beneficial to many digital applications such as, for example, in cameras, scanners, machine vision systems, vehicle navigation systems, video telephones, computer input devices, surveillance systems, auto focus systems, star trackers, motion detection systems, image stabilization systems and data compression systems for high-definition television. 
   CMOS imagers have a low voltage operation and low power. consumption; CMOS imagers are compatible with integrated on-chip electronics (control logic and timing, image processing, and signal conditioning such as A/D conversion); CMOS imagers allow random access to the image data; and CMOS imagers have lower fabrication costs as compared with, for example, the conventional CCD since standard CMOS processing techniques can be used. Additionally, low power consumption is achieved for CMOS imagers because only one row of pixels at a time needs to be active during the readout and there is no charge transfer (and associated switching) from pixel to pixel during image acquisition. On-chip integration of electronics is particularly advantageous because of the potential to perform many signal conditioning functions in the digital domain (versus analog signal processing) as well as to achieve a reduction in system size and cost. 
   A CMOS imager circuit includes a focal plane array of pixel cells, each one of the cells including a photosensor, for example, a photogate, photoconductor or a photodiode overlying a substrate for accumulating photo-generated charge in the underlying portion of the substrate. Each pixel cell has a readout circuit that includes at least an output field effect transistor formed in the substrate and a charge storage region formed on the substrate connected to the gate of an output transistor. The charge storage region may be constructed as a floating diffusion region. Each pixel may include at least one electronic device such as a transistor for transferring charge from the photosensor to the storage region and one device, also typically a transistor, for resetting the storage region to a predetermined charge level prior to charge transference. 
   In a CMOS imager, the active elements of a pixel cell perform the necessary functions of: (1) photon to charge conversion; (2) accumulation of image charge; (3) resetting the storage region to a known state; (4) selection of a pixel for readout; and (5) output and amplification of a signal representing pixel charge. The charge at the storage region is typically converted to a pixel output voltage by the capacitance of the storage region and a source follower output transistor. 
   CMOS imagers of the type discussed above are generally known as discussed, for example, in U.S. Pat. Nos. 6,140,630, 6,376,868, 6,310,366, 6,326,652, 6,204,524 and 6,333,205, assigned to Micron Technology, Inc., which are hereby incorporated by reference in their entirety. 
     FIG. 1  illustrates a block diagram for a CMOS imager  10 . The imager  10  includes a pixel array  20 . The pixel array  20  comprises a plurality of pixels arranged in a predetermined number of columns and rows. The pixels of each row in array  20  are all turned on at the same time by a row select line and the pixels of each column are selectively output by a column select line. A plurality of row and column lines are provided for the entire array  20 . 
   The row lines are selectively activated by the row driver  32  in response to row address decoder  30  and the column select lines are selectively activated by the column driver  36  in response to column address decoder  34 . Thus, a row and column address is provided for each pixel. The CMOS imager  10  is operated by the control circuit  55 , which controls address decoders  30 ,  34  for selecting the appropriate row and column lines for pixel readout, and row and column driver circuitry  32 ,  36 , which apply driving voltage to the drive transistors of the selected row and column lines. 
   Each column contains sampling capacitors and switches  38  associated with the column driver  36  that reads a pixel reset signal Vrst and a pixel image signal Vsig for selected pixels. A differential signal (Vrst-Vsig) is produced by differential amplifier  40  for each pixel and is digitized by analog-to-digital converter  45  (ADC). The analog-to-digital converter  45  supplies the digitized pixel signals to an image processor  50 , which forms a digital image output. 
   In order to maintain the quality and brightness of an image at an optimal level, the exposure and gain settings have to be continually adjusted for varying light conditions. Exposure is the duration for which the pixel sensor is capturing photons and accumulating induced electrons. Gain is the amount of analog amplification or attenuation that a pixel sensor signal undergoes. Amplification is where the gain is greater than one and attenuation is where the gain is less than one. 
   By varying the exposure and the gain of a pixel sensor, optimal images can be obtained from a sensor. For example, for the bright light conditions of a beach on a sunny day, the exposure would be set to a minimum and the gain to less than or equal to one. Similarly, if the image desired to be captured is a polar bear in a snow storm, the exposure would be set to a minimum and the gain to less than or equal to one. For dark conditions such as when trying to capture an image of a deer at night, the exposure would be set to a maximum and the gain to greater than or equal to one. Automatic exposure and gain control algorithms, however, carry the risk of oscillations. If the desired exposure and gain and the actual exposure and gain do not converge, then oscillations result, which adversely impact the captured image. 
   Accordingly, there is a need and desire for improved automatic exposure and gain control in imaging devices such as CMOS imagers. 
   SUMMARY 
   The invention provides improved automatic exposure and gain control in imaging devices such as CMOS imagers. 
   The above and other features and advantages are achieved in various exemplary embodiments of the invention by providing an apparatus and method for performing automatic exposure control based on current measured luminance of an image and dynamic/modifiable target luminance levels. Exposure adjustments and/or adjustments to the dynamic/modifiable target luminance windows are based on the measured luminance and threshold settings to improve image quality while avoiding oscillations and other problems typically associated with automatic exposure control. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The foregoing and other advantages and features of the invention will become more apparent from the detailed description of exemplary embodiments provided below with reference to the accompanying drawings in which: 
       FIG. 1  is a block diagram illustrating a typical CMOS imager; 
       FIG. 2  is a block diagram illustrating a CMOS imager having automatic exposure control; 
       FIG. 3  illustrates an average-luminance-based method of performing automatic exposure control; 
       FIG. 4  illustrates an improved average-luminance-based method of performing automatic exposure control in accordance with a first exemplary embodiment of the invention; 
       FIG. 5  illustrates an improved average-luminance-based method of performing automatic exposure control in accordance with a second exemplary embodiment of the invention; 
       FIG. 6  illustrates a method of calculating maximum color in accordance with an exemplary embodiment of the invention; 
       FIG. 7  illustrates a method of calculating maximum color in accordance with another exemplary embodiment of the invention; 
       FIG. 8  illustrates a method of calculating maximum color in accordance with yet another exemplary embodiment of the invention; and 
       FIG. 9  shows a processor system incorporating at least one imaging device constructed in accordance with an embodiment of the invention. 
   

   DETAILED DESCRIPTION 
     FIG. 2  illustrates a CMOS imager  110  having automatic exposure control. The imager  110  includes a pixel array  120  comprising a plurality of pixels arranged in a predetermined number of columns and rows. The pixels of each row in array  120  are all turned on at the same time by a row select line and the pixels of each column are selectively output by a column select line. A plurality of row and column lines are provided for the entire array  120 . 
   The row lines are selectively activated by the row driver  132  in response to row address decoder  130  and the column select lines are selectively activated by the column driver  136  in response to column address decoder  134 . Thus, a row and column address is provided for each pixel. The CMOS imager  110  is operated by the control circuit  155 , which controls address decoders  130 ,  134  for selecting the appropriate row and column lines for pixel readout, and row and column driver circuitry  132 ,  136 , which apply driving voltage to the drive transistors of the selected row and column lines. 
   Each column contains sampling capacitors and switches  138  associated with the column driver  136  that reads a pixel reset signal Vrst and a pixel image signal Vsig for selected pixels. A differential signal (Vrst-Vsig) is produced by differential amplifier  140  for each pixel and is digitized by analog-to-digital converter  145  (ADC). The analog-to-digital converter  145  supplies the digitized pixel signals to an image processor  150 , which forms a digital image output. 
   To perform automatic exposure control, an automatic exposure control block  160  is connected to receive pixel signal information from the image processor  150 . It should be appreciated that the automatic exposure control block  160  may be part of the image processor&#39;s  150  logic, or it may be a separate piece of hardware and/or logic. The output of the automatic exposure control block  160  is used to set registers  162  used by the timing and control circuit  155  to control image exposure and gain settings. An example of an imager containing automatic exposure and gain control can be found in U.S. Patent Application Publication no. 2005/0057666, which is hereby incorporated by reference. 
   According to one method  200 , illustrated in  FIG. 3 , the primary automatic exposure control technique is based upon measuring the center weighted average of the luminance of the image, and comparing the average to a desired static target luminance. Method  200  could be implemented in the automatic exposure control block  160  illustrated in  FIG. 2 . Luminance is a linear combination of the red, blue and green (“RGB”) color components of an image. Luminance is typically referred to as Y for historical reasons. When the RGB components have been gamma corrected, then luminance Y is referred to as luma Y′.  FIG. 3  illustrates “Luma” in method  200 , but for convenience purposes only, the method  200  is now described with reference to luminance. It should be appreciated that luminance values or luma values could be used as desired. 
   A detailed explanation of method  200  now follows. At step  202 , the image&#39;s luminance is measured and then compared to a static target luminance at step  204 . This check serves as a threshold trigger that must be met before auto exposure takes place. That is, image statistics are observed, image frame by image frame, until the statistics deviate from a nominal condition by a predetermined amount. Specifically, step  204  determines if the absolute value of the difference between the measured luminance and the target luminance is greater than a predetermined threshold. If the absolute value of the difference between the measured luminance and the target luminance is not greater than the threshold, method  200  continues at step  202  where the image&#39;s luminance is measured again. If the absolute value of the difference between the measured luminance and the target luminance is greater than the threshold, method  200  continues at step  206  where the measured image luminance is compared to a test luminance. If the measured image luminance is less than the test luminance, image exposure time is increased (by setting the appropriate registers  162 ) at step  208 . If the measured image luminance is greater than the test luminance, image exposure time is decreased (by setting the appropriate registers  162 ) at step  214 . 
   Once the image exposure time has been increased/decreased, the image&#39;s luminance is measured again at step  210 . At step  212 , it is determined if the measured luminance is approximately equal to the target luminance (i.e., plus or minus a predetermined window). If the measured luminance is approximately equal to the target luminance, method  200  continues at step  202 . If the measured luminance is not approximately equal to the target luminance, method  200  continues at step  206 . 
   In general, method  200  is not robust enough and can lead to over and under exposed images. As such, method  200  is not desirable, A solution to this problem is to organize the pixel luminance statistics into a histogram, and use the histogram as the basis for exposure control, with the heuristic of pushing the exposure up to the point where pixels just begin to saturate (from excessive brightness). However, a full luminance histogram (with bins for every luminance value) is memory excessive and is also undesirable. 
   The inventor has devised a solution to the above automatic exposure control issues. As is explained below in more detail with respect to  FIGS. 4 and 5 , a smaller set of statistics, which directly pertain to image exposure, are obtained and processed by the present invention. In the present invention, exposure is moved in the proper direction by modest amounts over multiple frames. 
   In the following methods, luminance is computed from the red, green, and blue color components using the following formula (although other legitimate formulations of luminance exist):
 
Luminance=0.586*Green+0.301*Red+0.113*Blue  (1)
 
   Instead of a full histogram, the present invention gathers four statistics. The first statistic is referred to as “current luminance” or “current average luminance,” which is the sum of pixel luminance values, center weighted to increase the influence of pixels within a region of interest (ROI), and normalized by the count of all pixels sampled. The second statistic is referred to as the “current saturated luminance,” which is the subset of the pixel luminance values that are “saturated” (pixels whose luminance value exceeds a high threshold), normalized by the count of all pixels collected (not the cardinality of the subset). 
   The above described prior center weighted average luminance method seeks to adjust exposure so that the measured current luminance is maintained within a range set by a target luminance±a luminance hysteresis. In other words, the stability window is static in position and width. The present invention, on the other hand, seeks to perform a similar analysis, but in addition, adjusts the target luminance value dynamically to support additional exposure criteria. 
   The additional exposure criteria include: (1) maintaining an exposure that results in a specified proportion (possibly 0%) of pixels being saturated; (2) bounding the target luminance on the high side to prevent excessive overlap of the luminance distribution with the saturated pixel range, which can occur in scene low dynamic range situations; and (3) bounding the target luminance on the low side to prevent excessive overlap of the luminance histogram with the black level, which can occur in scene high dynamic range situations. 
   The additional control settings necessary for the dynamic target luminance based method of the invention include: (1) a saturation threshold, which determines the threshold luminance value above which a pixel is collected as a part of the current saturated luminance statistic; (2) a saturation high water mark, which is the maximum proportion of saturated pixels considered acceptable in an image; (3) an upper limit on target luminance; and (4) a lower limit on target luminance. 
   In order to avoid feedback oscillations due to adjusting exposure and target luminance simultaneously, the dynamic target luminance method of the invention is applied as “polishing” steps to a center weighted average luminance method. Generally, these steps can be described as follows. For the first polishing step, when the current luminance moves outside the range of the target luminance stability window, the exposure is adjusted to move it back within bounds. The stability window for the target luminance extends from two exposure steps down from the target luminance to two exposure steps up from the target luminance. Regarding the second polishing step, when the current luminance moves just past the target luminance (i.e., the center of the hysteresis window), the dynamic target luminance kicks in (described below in more detail). 
   As a third polishing step, if the current saturated luminance is less than the saturation high water mark, then the target luminance is increased by one exposure step and the exposure settings are adjusted to track this change. This step is repeated in subsequent frames until the current saturated luminance is greater than or equal to the saturation high water mark, or the upper limit on target luminance is reached. 
   As a fourth polishing step, the target luminance is decreased by one exposure step and the exposure settings are adjusted to track this change. This step is repeated in subsequent frames until the current saturated luminance is less than the saturation high water mark, or the lower limit on target luminance is reached. 
   With reference to  FIG. 4 , a method  300  of performing automatic exposure control having dynamic target luminance in accordance with an exemplary embodiment of the invention is now described.  FIG. 4  illustrates “Luma” in method  300 , but for convenience purposes only, the method  300  is now described with reference to luminance. In addition, for steps  306 - 316 , max color component is substituted for luminance for all cases except for black and white pixel counts (described in more detail below with reference to  FIGS. 4 and 5 ). It should be appreciated that luminance values or luma values could be used as desired. In addition, “maximum color saturation” as used below refers to the relative proportion of pixels whose maximum color component exceeds a saturation value. The method  300  may be executed by the automatic exposure control block  160  illustrated in  FIG. 2 . 
   At step  302 , the image&#39;s luminance is measured and then compared to a target luminance at step  304 . This check serves as a threshold trigger that must be met before auto exposure takes place. That is, image statistics are observed, image frame by image frame, until the statistics deviate from a nominal condition by a predetermined amount. Specifically, step  304  determines if the absolute value of the difference between the measured luminance and the target luminance is greater than a predetermined threshold. If the absolute value of the difference between the measured luminance and the target luminance is not greater than the threshold, method  300  continues at step  302  where the image&#39;s luminance is measured again. Measuring includes collecting the image statistics from a new frame or frames. If the absolute value of the difference between the measured luminance and the target luminance is greater than the threshold, method  300  continues at step  306  where it is determined if the measured image luminance is less than the target luminance. If the measured luminance is less than the target luminance, image exposure is increased by one step at step  320  and the method  300  continues at step  340  where the maximum color is measured. Measuring includes collecting all image statistics from a new frame or frames. 
   If at step  306 , it is determined that the measured luminance (i.e., maximum color component) is not less than the target luminance, the method  300  continues at step  308  where it is determined if the measured luminance is greater than the target luminance plus a predetermined threshold. If it is determined that the measured luminance is greater than the target luminance plus the threshold, image exposure is decreased by one step at step  322  and the method continues at step  340 . 
   If at step  308  it is determined that the measured luminance is not greater than the target luminance plus the threshold, method  300  continues at step  310  where the maximum color saturation is compared to the maximum limit. If the maximum color saturation is greater than the maximum limit, the target luminance is increased at step  324  and the method continues at step  340 . If at step  310  the maximum color saturation is not greater than the maximum limit, the method  300  continues at step  312  where it is determined if the measured luminance is greater than the target luminance. If it is determined that the measured luminance is greater than the target luminance, image exposure is decreased by one step at step  326  and the method  300  continues at step  342  where the maximum color is measured. Measuring includes collecting all image statistics from a new frame or frames. 
   If at step  312  it is determined that the measured luminance is not greater than the target luminance, it is then determined if the measured luminance is less than the target luminance minus the threshold (step  314 ). If the measured luminance is less than the target luminance minus the threshold, the image exposure is increased by one step at step  328  and the method  300  continues at step  342 . If the measured luminance is not less than the target luminance minus the threshold, method  300  continues at step  316  where the maximum color saturation is compared to the maximum limit. If the maximum color saturation is greater than the maximum limit, the target luminance is decreased at step  330  and the method  300  continues at step  342 . If at step  316  the maximum color saturation is not greater than the maximum limit, the method  300  continues at step  302 . 
   Thus, as can be seen from the  FIG. 4  method  300 , in a first exemplary embodiment of the invention, a dynamic target luminance is used to bolster the automatic exposure control of the invention. The illustrated embodiment, however, may be further refined to compensate for additional factors that may affect automatic exposure control. For example, testing has determined that when there is a large dynamic range of luminance values in the scene, small areas of very bright pixels could drive the exposure down to the point that the majority of the scene is underexposed. In order to address this issue, a “black alarm” is added to the  FIG. 4  method  300  to produce method  400  (illustrated in  FIG. 5 ). The black alarm seeks to maintain a balance between white (bright) pixels and black (dark) pixels. Generally, this corresponds to centering the dynamic range of the sensor within the larger dynamic range of the scene. Visually this means that some bright areas of the scene will be saturated, and some dark areas of the scene will be black. 
   In a preferred embodiment of the invention, the black alarm is added as an additional stopping criteria to step  316  ( FIG. 4 ) to form step  416  of method  400 . In addition, black alarm checking is also added to step  310  ( FIG. 4 ) to form step  410  of method  400 . If the count of the “black pixels” exceeds the count of the “white pixels” plus a “black pad” value, then the black alarm is triggered and further decreases in target luminance are prohibited. 
   The black pad is a bias to the black alarm calculation that minimizes the chance that small quantities of white and black pixels can destabilize the triggering of the black alarm. In the following explanation, it is assumed that we are analyzing a luminance histogram, the bulk of which is narrowly concentrated around a central luminance value. In addition, there are a few pixels that are very dark and a few pixels that are very bright. Random noise in the luminance distribution will shift the balance between white and black pixels practically on every frame. To keep this from happening, the black pad is added into the count of white pixels, to act as a tolerance. In other words, the number of black pixels must significantly exceed the number of white pixels before the black alarm is triggered. The black pad is implemented as a percentage of the total number of pixels collected, so that its value scales with the sample set cardinality. 
   The additional statistics collected for the black alarm implementation include: (1) a white count, which is a count of the number of pixels whose luminance value is greater than or equal to a white threshold value; and (2) a black count, which is a count of the number of pixels whose luminance value is less than or equal to a “black” threshold value. 
   The additional control settings necessary for the implementation of the black alarm include: (1) a white threshold, which determines the threshold luminance value above which a pixel increments the white count; (2) a black threshold, which determines the threshold luminance below which a pixel increments the black count; and (3) the black pad, which is a bias in the black alarm calculation that minimizes the chance that small quantities of white and black pixels can destabilize the triggering of the black alarm. 
   Luminance is the prime quantity being measured in the above methods  300 ,  400 . The reason for controlling exposure based upon luminance saturation is the limited dynamic range of the pixels and the digital representation of the pixel values. Either the physical pixel well itself could saturate, or the analog-to-digital converter  145  ( FIG. 2 ) could saturate. 
   Since the pixels come in three varieties (e.g., red, green, and blue), it follows that the individual color channels might saturate at different luminance values, due to variations in quantum efficiency, the amount of analog gain applied to individual color channels, and the differential contribution of the color channels to the luminance value. So if a sensor is pointed at a clear blue sky, the 11% contribution of the blue channel to the luminance means that the blue channel will saturate long before the luminance value itself saturates. This will be perceived as a shift in the sky color, as first the green then the red channels saturate with increasing exposure. 
   There are several possible ways to replace luminance as the measured quantity in order to address the above issue. For example, referring now to method  500  illustrated in  FIG. 6 , separate saturation statistics for each color component may be collected (steps  502 ,  504 ,  506 ), and then the maximum of the three saturation percentages (step  508 ) is compared to the high water mark (i.e., maximum permitted percentage) at step  510 . 
   An alternative method  600  is illustrated in  FIG. 7 . In method  600 , the maximum of the three color components of each pixel is collected (step  602 ), instead of the luminance. The percentage of values exceeding a predetermined saturation threshold is computed (step  604 ) and compared to the high water mark (i.e., maximum permitted percentage) at step  606 . 
     FIG. 8  illustrates another alternative method  700  where all three components of each pixel are collected and treated like individual luminance values. The percentage of values exceeding a predetermined saturation threshold is computed (step  702 ) and compared to the high water mark (i.e., maximum permitted percentage) at step  704 . 
   It should be notes that the RGB pixel colors experience at least one transformation (and possibly more) in color space. At the minimum, RGB information is converted to YCbCr color space via a linear transformation. This can be viewed as taking a three-dimensional RGB color cube, and then rotating and skewing the cube. The result is that there are colors in RGB color space that cannot be represented in YCbCr color space. This can be illustrated by thinking of the corners of the one color cube poking out the sides of the transformed color cube. The intersection of the two color spaces is known as the representable “gamut” of colors. 
   To address this, the non-representable colors are individually transformed into near analog colors of the destination color space. The approach usually taken is to de-saturate the color, i.e., make it more pastel by moving it closer to a gray color of similar luminance value. This process is sometimes referred to as color kill or color filtering. 
   The brighter a color is in luminance, the greater the chance that it might fall outside the destination color space. So if a scene is composed of highly color saturated (vibrant) colors, increasing the exposure increases the chances that pixels will need to be transformed to bring them back into gamut. Therefore, an additional criterion to limit the increase in exposure would be to measure how many pixels are being transformed, and if the percentage exceeds some threshold, prohibit further increases in target luminance. 
   The present invention has been described as increasing and decreasing exposure settings. It should be appreciated that the settings may be set via registers  162  ( FIG. 2 ) or software tables/variables. It should be appreciated that the type of exposure adjustment step is application specific and should not limit the invention. One exemplary exposure adjustment step could include a step that is plus or minus 1/16 th  the current exposure level. It should be appreciated that the predetermined thresholds, high water marks, etc. described above may also be programmable and stored in registers  162  ( FIG. 2 ) or software tables/variables. 
     FIG. 9  shows system  1000 , a typical processor system modified to include an imaging device  1008  constructed in accordance with one of the embodiments of the invention (i.e., CMOS imager  110  illustrated in  FIG. 2  performing one of or a combination of the automatic exposure control methods  300 ,  400 ,  500 ,  600  and  700  of the invention). The processor system  1000  is exemplary of a system having digital circuits that could include image sensor devices. Without being limiting, such a system could include a computer system, camera system, scanner, machine vision, vehicle navigation, video phone, surveillance system, auto focus system, star tracker system, motion detection system, image stabilization system, and data compression system. 
   System  1000 , for example a camera system, generally comprises a central processing unit (CPU)  1002 , such as a microprocessor, that communicates with an input/output (I/O) device  1006  over a bus  1020 . Imaging device  1008  also communicates with the CPU  1002  over the bus  1020 . The processor system  1000  also includes random access memory (RAM)  1004 , and can include removable memory  1014 , such as flash memory, which also communicate with the CPU  1002  over the bus  1020 . The imaging device  1008  may be combined with a processor, such as a CPU, digital signal processor, or microprocessor, with or without memory storage on a single integrated circuit or on a different chip than the processor. It should be appreciated that the invention may be implemented in other imaging devices such as e.g., CCD imagers. Thus, the invention is not limited to the illustrated CMOS imager examples. 
   The processes and devices described above illustrate preferred methods and typical devices of many that could be used and produced. The above description and drawings illustrate embodiments, which achieve the objects, features, and advantages of the present invention. However, it is not intended that the present invention be strictly limited to the above-described and illustrated embodiments. Any modification, though presently unforeseeable, of the present invention that comes within the spirit and scope of the following claims should be considered part of the present invention.

Technology Classification (CPC): 7