Abstract:
An oversampling A to D converter device. A succesive approximation A to D converter system is used with a relatively small size, and low resolution succesive approximation A to D converter. This converter is operated at a higher speed to obtain multiple samples and obtain additional bits of resolution from said multiple samples. Another aspect adds noise to the circuit, to cancel out noise.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of the U.S. Provisional Application No. 60/106,490, filed on Oct. 29, 1998. 
    
    
     BACKGROUND 
     An active pixel sensor typically takes the form shown in FIG. 1. A photosensor array  101  is disposed on a single chip substrate  100  with a number of columns  102  and rows  104 . Each pixel has a photoreceptor  122 , a follower transistor  124 , and a selection transistor  126 . 
     The pixels from the photosensor are coupled to one or more analog to digital converters  110  which convert the analog information  106  from the sensor  100  into digital output information  112 . The analog to digital converters  110  are typically on the same substrate  100  with the image sensor  100 . In a particularly preferred architecture, as shown, one analog to digital converter is associated with each column of the array. This system operates in column-parallel mode. At each clock cycle, an entire row of information is simultaneously output from the bank of analog to digital converters. The accuracy of the output image, which is collectively obtained from the output of all the analog to digital converters, is therefore dependent on the accuracy of the analog to digital converters. These devices, however, are limited in size. They must fit on the substrate. They also need to be relatively fast to maintain the processing speed. 
     SUMMARY OF THE INVENTION 
     The present invention teaches a system of introducing statistical processing into the A/D converters in order to improve the overall image quality. This is done according to the present invention by using A/D converters that are configured to oversample the input signal, find a centroid of the oversampled signal, and use the oversampling to enhance the accuracy. 
     The ADCs can operate with fewer bits than required for the total output, since oversampling is carried out. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     These and other aspects of the invention will be described in detail with reference to the accompanying drawings, wherein: 
     FIG. 1 shows an active pixel sensor block diagram; 
     FIG. 2 shows a block diagram of the oversampling operation; 
     FIG. 3 shows a block diagram of another system using random noise addition; 
     FIGS. 4 a - 4   c  illustrate the operation. 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     An embodiment is shown in FIG. 2. A photosensor array  200  can be for example, an active pixel sensor of the type described above and as described in U.S. Pat. No. 5,471,515, and shown in FIG.  1 . The sensor is arranged to produce output signals  205 . One output signal can be produced at any one time using a fast A to D converter, such as a flash type ADC, or output signals can be produced in a column-parallel manner. 
     Each output signal such as  205  is coupled to an A to D converter  210 . The A to D converter  210  has a specified resolution, e.g. a resolution less than that desired for the total output. 
     In this embodiment, A to D converter  210  has a resolution of 7 bits shown as the output  216 . The A to D converter is driven by a clock  215  which operates at frequency faster than the production of signal  205 . For example, the clock may operate  16  times faster or 64 times faster than the speed at which the output signal  205  is produced. Therefore, each output signal, for example, is oversampled by 16 times or 64 times. 
     The results are stored in buffer  225 , operated on by interpolator  230 . Interpolator effectively averages the values in the buffer  225  so that the noise that is mixed with the signal is effectively averaged out. The averaged signal therefore has improved accuracy. 
     Moreover, since the number of bits needed for actual accuracy of the A/D converter is reduced, the A/D converter  210  can be made smaller and faster. According to a preferred embodiment, a 16 times oversampling is used to obtain three extra bits of image quality. In addition, image quality is increased by lower quantization distortion, and lower quantizing distortion. Dithering can also be used to improve the contouring. 
     An embodiment can use a 7 bit A/D converter, which is driven by the clock to oversample by sixteen times (16×). 
     The interpolator  230  is a standard digital interpolator as known in sigma delta A/D converters, for example. The 16 times oversample is interpolated to produce a 10-bit output at 235. An important advantage is that since the A/D converter  210  operates with fewer bits, it can be a successive approximation A/D converter which can operate with smaller capacitors. By using smaller capacitors, the amount of real estate on the chip substrate is decreased. In addition, the smaller capacitors take less time to charge. Since less space is taken up by the A to D converter, the ratio of the digital area to the analog area of the chip is increased. This helps to make the overall design more scalable to smaller CMOS features. 
     Another embodiment is shown in FIG.  3 . The analog signal  205  is connected to an analog adder  310  (e.g., a node) where it is added to noise produced by noise generator  312 . The bias signal  314  applied to the adder  310  can be a representation of the noise in the system, to cancel out some of that noise. The level-adjusted analog signal  315  is then coupled to 7 bit A to D converter  210 , which has a least significant bit resolution of 8 millivolts. 
     The output signal is coupled to a digital adder  330  which adds the output sample to previous samples. M samples are added, where here M can equal 16. The digital adder produces a digital output of N=10 bits, with the least significant bit (LSB)=1 millivolt. 
     This bias input  312  can be a bias level, or can be random noise with an RMS equal to half the value of the least significant bit. 
     The present system has described M=16 in order to obtain three additional bits of resolution. More generally, the number of required summations may be obtained from the equation for desired Dynamic Range Extension: 
     
       
           D =log 2 (2 ·{square root over (M)} )=1+0.5·log 2   M   
       
     
     The most reasonable selection for the standard TV application could be 3-bits, requiring 16 summations. 
     Other possible values are: 
     
       
         
               
               
               
             
               
               
               
             
           
               
                   
                   
               
               
                   
                                M 
                 D, bit 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                   
                                8 
                 2.5 
               
               
                   
                 16 
                 3 
               
               
                   
                 32 
                 3.5 
               
               
                   
                 64 
                 4 
               
               
                   
                   
               
             
          
         
       
     
     FIGS. 4A-4C show the operation of the oversampling centroid A to D converter. FIG. 4A shows the initial distribution, where the half LSB equals 4 millivolts. After 16 summations, the least significant bit is one millivolt, but the values have changed, as shown in FIG.  4 B. FIG. 4C shows shifting right by one bit to produce the final output. 
     Quantizing distortion is often visible as contouring. The quantizing distortion is often countered by a technique called dither. Dither adds white noise to the signal. However, this dither reduces the signal to noise ratio. 
     Other embodiments are within the disclosed embodiment.