Method and apparatus for implementing two-dimensional digital filters

Abstract: A structure for implementing a plurality of two-dimensional digital filters, such as finite impulse response filters, in an efficient manner. The structure includes a plurality of first stage filters operating in a first dimension in combination with a single second stage filter, operating in a second dimension. The second stage filter being suitable for receiving output from one of the first stage filters. A controller, operating in conjunction with the first and second stage filters is utilized for controlling the operation of all filters, as well as the selection of the input source for the second stage filter.

Description: This invention relates generally to a digital signal processing apparatus, and more particularly to the implementation of a plurality of two-dimensional digital filters using a series of one-dimensional transformations. The features of the present invention may be used in the printing arts and, more particularly, in digital image processing and electrophotographic printing. In digital image processing there is a distinct advantage to being able to provide digital filtering in an efficient and low cost manner. With regard to efficiency, it is advantageous to design hardware implementations of digital filters that are efficient. This efficiency has two factors, first a speed of processing factor, and second a hardware minimization factor. Accordingly, the present invention provides a two-dimensional digital filter that is efficient with respect to processing speed and hardware implementation, as well. Signal processing devices usually require filters, especially two-dimensional filters to process data in numerous ways. Well known electrophotographic systems, for example, the Xerox® Docutech Production Publisher,® usually employ digital hardware and application specific integrated circuit (ASIC) devices specifically designed to provide digital filtering capabilities. Generally, this type of system would employ hardware, software, or a combination of both to implement the digital filtering capabilities required. Various approaches have been devised for the implementation of digital filtering techniques, of which the following disclosures appear to be relevant: US-A-4,766,561 to Thompson et al. discloses a circuit for performing a plurality of finite impulse response filtering functions. US-A-4,777,612 to Tomimitsu discloses a digital signal processing apparatus for providing high-speed digital filtering. US-A-4,821,223 to David describes a two-dimensional finite impulse response filter having a plurality of filter portions of substantially identical construction arranged in a parallel configuration. The present invention seeks to overcome the limitations of the related references by providing a plurality of one-dimensional (1-D) transform units that may be selectively combined with an additional one-dimensional transform unit to produce a plurality of distinct two-dimensional (2-D) filters, any one of which is selectable on a pixel by pixel basis. Moreover, the present system has the added advantage of providing these two-dimensional finite impulse response filters without employing multiple, identically constructed two-dimensional filters arranged in a parallel fashion, thereby substantially reducing the complexity and cost of the filter hardware. In accordance with one aspect of the present invention, there is provided an image processing device according to claim 1 of the appended claims. A particular embodiment is provided according to claim 2 of the appended claims. Preferably, the second dimension filter includes means, operative on a pixel by pixel basis, for selecting the context buffer to be used for data input to the second dimension filter; means for adding symmetric values within the context buffer value to produce a sum; means for latching the resultant sums of the symmetric values; means for multiplying the latched sums by predetermined filter coefficients; and means for accumulating the products output by the multiplication means, to produce an output for the second dimension filter. Preferably, the multiplication means operates at a rate greater than the incoming data rate, thereby enabling a single multiplication means to sequentially produce all of the multiplication products during a single input data cycle. The image processing device may further comprise means for scaling the output of the second dimension filter in accordance with a predetermined scale factor; and means, suitable for the detection of overflow and underflow conditions, for correcting such conditions when present in the output of the second dimension filter. A further particular embodiment is provided according to claim 3 of the appended claims. Preferably, each of the plurality of first stage filters includes means for latching the input pixel signals; means for combining symmetric pairs of the latched input pixel signals to produce a signal representative of the sum of the symmetric signals; means for latching the resultant sums of the symmetric pair signals; means for multiplying the latched sums by predetermined filter coefficients; and means for accumulating the signals representing the products output by the multiplication means, to produce an accumulated output signal for the first stage filter. Preferably, the the second stage filter includes means, operative on a pixel signal by pixel signal basis, for selecting the context buffer to be used for input to the second stage filter; means for combining symmetric signals within the context buffer value to produce a signal representative of the sum of the symmetric signals; means for latching the resultant sums of the symmetric signals, means for multiplying the latched sums by predetermined filter coefficients; and means for accumulating the signals representing the products output by the multiplication means, to produce an an accumulated output for the second stage filter. Preferably, the multiplication means operates at a speed greater than the incoming signal frequency, thereby enabling a single multiplication means to sequentially produce all of the multiplication products during a single input signal cycle. The filter device may further comprise means for scaling the output of the second stage filter in accordance with a predetermined scale factor; and means for detecting overflow and underflow conditions in the output signal of the second stage filter and for correcting such conditions when detected. The filter device may further comprise a plurality of input pixel signal buffers suitable for storing incoming pixel signals in a manner consistent with the establishment of sufficient context so as to enable the accurate operation of the first stage filters. A further particular embodiment is provided according to claim 7 of the appended claims. Preferably, each of the plurality of first dimension filters includes means for latching the input digital image data; means for adding symmetric pairs of the latched data values to produce a sum; means for latching the resultant sums of the symmetric pair values; means for multiplying the latched sums by predetermined filter coefficients; and means for accumulating the products output by the multiplying means, to produce an output for the one-dimensional filter. Preferably, the subsequent second dimension filter includes means, operative on an element by element basis, for selecting the context storage means to be used for data input to the subsequent one-dimensional filter; means for adding symmetric element values within the context storage means value to produce a sum; means for latching the resultant sums of the symmetric values; means for multiplying the latched sums by predetermined filter coefficients; and means for accumulating the products output by the multiplication means, to produce an output for the subsequent one-dimensional filter. Preferably, the multiplying means operates at a rate greater than the incoming data rate, thereby enabling a single multiplying means to sequentially produce all of the multiplication products during a single data input cycle. The apparatus may further comprise means for scaling the output of the subsequent one-dimensional filter in accordance with a predetermined scale factor; and means for detecting overflow and underflow conditions and for correcting such conditions when present in the output of the second dimension filter. A further particular embodiment is provided according to claim 8 of the appended claims. Preferably, each of the plurality of first dimension filters includes means for latching the m digital input signals; means for adding symmetric pairs of the latched signals to produce a sum; means for latching the resultant sums of the symmetric pair values; means for multiplying the latched sums by their respective coefficients from the set of filter coefficients; and means for accumulating the products output by the multiplying means, to produce an output for the first dimension filter. Preferably, the n element second dimension filter includes means, operative on a signal by signal basis, for selecting the context buffer to be used for data input to the n element filter; means for adding symmetric element values within the context buffer to produce a sum; means for latching the resultant sums of the symmetric values; means for multiplying the latched sums by their respective coefficients from the set of filter coefficients; and means for accumulating the products output by the multiplication means, to produce an output for the n element second dimension filter. Preferably, the multiplying means operates at a rate greater than the incoming digital signal rate, thereby enabling a single multiplying means to sequentially produce all of the multiplication products during a single signal input cycle. The apparatus may further comprise means for scaling the output of the n element second dimension filter in accordance with a predetermined scale factor; means for the detection of overflow and underflow conditions; and means for correcting such conditions when present in the output of the second dimension filter. The present invention further provides a method for implementing a plurality of two-dimensional digital filters according to claim 10 of the appended claims. Preferably, the method includes the steps of receiving the digital signals from an external source; storing the digital signals in an array of digital recording elements, said array providing access to the digital signals along a specific orientation; and retrieving one or more of the digital signals stored in the array, for use as the input digital signals for the plurality of one-dimensional filters. Preferably, the method may include the steps of scaling the output of the additional second dimension filter in accordance with a predetermined scale factor; detecting overflow and underflow conditions in the output of the additional one-dimensional filter; and correcting for the overflow and underflow conditions, when detected. Figure 1 is a schematic illustration of an image processing hardware module incorporating the two-dimensional filter of the present invention; Figure 2 is a block diagram illustrating the components used in the prior art implementations of two-dimensional filters; Figure 3 is a block diagram illustrating the reduced hardware component set used in the present invention for implementation of a pair of two-dimensional filters; Figures 4A and 4B are more detailed illustrations of the hardware components used to implement the slow scan filters of figure 3; Figure 5 is a detailed representation of the context storage buffer for the pair of slow scan filters of figure 4A; Figure 6 is an illustration of the hardware components used to implement the single fast scan filter of figure 3; and Figure 7 is a flow diagram illustrating the equivalent steps associated with the operation of the two-dimensional filters of the present invention. The following description includes references to slow scan and fast scan digital image data when discussing the directionality of the two-dimensional filtering architecture. For purposes of clarification, fast scan data is intended to refer to individual pixels located in succession along a raster of image information, while slow scan data refers to data derived from a common raster position across multiple rasters or scanlines. As an example, slow scan data would be used to describe signals captured from a plurality of elements along a linear photosensitive array as the array was moved relative to a document. On the other hand, fast scan data would refer to the sequential signals collected along the length of the linear photosensitive array during a single exposure period, and is also commonly referred to as a raster of data. In the drawings, like reference numerals have been used throughout to designate identical elements. Figure 1 schematically depicts the various components of a digital image processing hardware module, such as might be used in a electrophotographic system for the processing and alteration of a video signal prior to its output. Referring now to Figure 1, which illustrates a possible image processing module architecture, image processing module 20 would generally receive offset and gain corrected video on input line 22. The video input data may be derived from a number of sources, including a raster input scanner, a graphics workstation, or electronic memory and similar storage elements. Moreover, the video input data in the present embodiment generally comprises 8-bit gray data, passed in a parallel fashion along the input data bus. Subsequently, module 20 would process the input video data according to control signals from CPU 24 to produce the output video signals on line 26. As illustrated, module 20 may include an optional segmentation block 30 which has an associated line buffer 32, two-dimensional filter 34, and an optional one-dimensional effects block, 36. Also included in module 20 is line buffer memory 38, comprising individual scanline buffers 42a-42e, for storing the context of incoming scanlines 1 through 5, respectively. Segmentation block 30, in conjunction with associated scanline buffer 32, which provides at least one scanline line of storage, is intended to parse the incoming video data to automatically determine those areas of the image which are representative of a halftone input region. Output from the segmentation block (Video Class) is used to implement subsequent image processing effects in accordance with the type or class of video signals identified by the segmentation block. For example, the segmentation block may identify a region containing data representative of an input halftone image, in which case a low pass filter would be used to remove screen patterns, otherwise, a remaining text portion of the input video image may be processed with an edge enhancement filter to improve fine line and character reproduction when thresholded. US-A-4,811,115 to Lin et al. (Issued March 7, 1989) teaches the use of an approximate auto-correlation function to determine the frequency of a halftone image area with respect to halftone image identification. One important aspect of incorporating the segmentation block in the image processing module is the requirement for a one scanline delay in video output. This requirement stems from the fact that the segmentation block needs to analyze the incoming line prior to determining the characteristics of the incoming video. Hence, the incoming corrected video is fed directly to segmentation block 30 while being delayed, for subsequent use by two-dimensional filter 34, in line buffer memory 38. Two-dimensional filter block 34, incorporating the elements of the present invention, is intended to process the incoming, corrected video in accordance with a predetermined filtering selection. As illustrated by line buffer memory 38, up to a total of 5 scanlines of incoming video data may be used to establish the context upon which the two-dimensional filter is to operate. Prior to establishment of the required scanline context, the input video bypasses the filter by using a bypass channel within the two-dimensional filter hardware. This bypass is necessary to avoid deleterious affects to the video stream that may result from filtering of the input video prior to establishing the proper context. Subsequent to two-dimensional filtering, the optional one-dimensional effects block is used to alter the filtered, or possibly unfiltered, video data in accordance with selected one-dimensional video effects. One-dimensional video effects include, for example, thresholding, screening, inversion, tonal reproduction curve (TRC) adjustment, pixel masking, one-dimensional scaling and other effects which may be applied one-dimensionally to the stream of video signals. As in the two-dimensional filter, the one-dimensional effects block also includes a bypass channel, where no additional effects would be applied to the video, thereby enabling the 8-bit filtered video to be passed through as output video. Control of the various combinations of "effects" and filter treatments to be applied to the video stream is enacted by CPU 24. Through the establishment of window tiles, various processing methods can be controlled by directly writing to control memory, from which the operation of the image processing blocks is regulated. More specifically, independent portions of the incoming video stream, portions selectable on a pixel by pixel basis, are processed in accordance with predefined image processing parameters. The selection of the specific parameters may be accomplished by selectively programming the features prior to or during the processing of the video stream. Also, the features may be automatically selected as previously described with respect to image segmentation block 30. In general, CPU 24 is used to initially program the desired image processing features, as well as, to update the feature selections during real-time processing of the video. In an alternative embodiment, the data for each pixel of image information may have an associated identifier or token to control the image processing operations performed thereon, as described in US-A-4,897,803 to Calarco et al. (Issued January 30, 1990) with respect to methods for controlling the processing of digital image data. Referring now to Figure 2, which displays the prior art approach for implementation of the two-dimensional digital filters, two independent filter channels, 60 and 62 are contained within the single two-dimensional filter hardware device, 34 of Figure 1. More importantly, in order to implement the pair of two-dimensional filters, of which only a single output is used at any time, two slow scan filters, 66a and 66b, operate on individual pixels within a particular scanline simultaneously. Subsequently, the outputs from slow scan filters 66a and 66b are passed to independent fast scan filters 68a and 68b, respectively. Individual application of fast scan filter coefficients 70a and 70b to filters 68a and 68b results in the filtered output of channels 60 and 62, respectively. Subsequently, the output of one of the channels is selected via multiplexer 72 in order to provide filtered video output on a pixel by pixel basis. While the illustration of the prior art may at first appear to be relatively efficient, from a hardware standpoint, it is important to consider what such a parallel filter architecture would require to implement n two-dimensional filtering operations, where any of n filters may be selected on a pixel by pixel basis. One can see that, although the slow scan filter of each channel is required to maintain the context of the data being filtered, the use of n fast scan filters is a purely redundant application of hardware. Hence the modified two-dimensional filter architecture of the present invention was developed to take advantage of the potential hardware reductions in an image processing module of this type. Figure 3, in conjunction with Figures 4A, 4B, 5, and 6, illustrates the hardware of the two-dimensional filter of the present invention. The hardware provides two independent five scanline by fifteen pixel finite impulse response (FIR), or convolution filters. Each filter allows for the use of a center pixel adjust coefficient, although filter coefficients must be symmetrical in both the fast and slow scan directions. The filter coefficients are programmable and may be set to zero to employ the use of a filter size smaller than 5 x 15. As previously described, the CPU may be utilized to program the operation of the filter to switch between filters or bypass them completely on a pixel by pixel basis. Each filter processes five input scanlines at a time, pixel by pixel, to calculate each output scanline. As previously described with respect to Figure 1, input scanlines must be buffered in line buffer 38 to meet the filter input requirements. In addition, if two-dimensional filter 34 is used with segmentation block 30 of Figure 1, the filter must operate one scanline later than the segmentation block. The two-dimensional convolution carried out by two-dimensional filter 34 may be expressed by the following equation: where m and n represent the two convolution dimensions. The two-dimensional filter implements the two-dimensional convolution under the condition that it is separable. Hence, the two-dimensional convolution of equation 1 may be expressed, as shown in equation 4, in terms of the following two one-dimensional convolutions (eq. 2, 3): where Pix(i,j) represents the input pixel values, and F(x,y) = g(x,y) + Pix(x,y)hc. (eq. 4) Referring now to Figures 3 through 6, which illustrate the reduced hardware implementation of the two-dimensional filter, input video is provided to slow scan filters 102a and 102b from line buffer memory 38 of Figure 1. Also provided to filters 102a and 102b are the associated slow scan filter coefficients, as contained in slow scan filter coefficient memory 104a and 104b, respectively. The slow scan filter coefficients are represented by the letters: A B C B A arranged in a symmetric fashion about the center scanline coefficient C . The output of slow scan filters 102a and 102b is directed to slow scan filter context buffers 106a and 106b respectively. As further illustrated in Figure 4A, slow scan filters 102a,b are actually implemented by identical hardware circuits and subsequently employ a multiplexed context switch, 208, to select the output from one of the two slow scan filters. Referring now to Figures 4A and 4B, which depict the first stage or slow scan filter hardware blocks, digital pixel data from the five scanlines or rasters (scanlines 0 - 5) is first latched at latches 150a, 150b, 150c, 150d, and 150e. The data latches for the outermost scanlines are paired with the mirror image scanline, for example, scanlines 0 and 4, and subsequently added at adders 152a,b. After summing the symmetrical scanlines, the results are again latched, latches 154a,b,c, and held for selection by multiplexer 156. Multiplexer 156 sequentially selects the results from latches 154a, 154b, and 154c, passing them to latch 158, where the values are retrieved for multiplication with their respective coefficients. For example, coefficients A 1 , B 1 , C 1 , output from coefficient multiplexer 162a, would be sequentially multiplied with the values in latch 158 by multiplier 164a, thereby producing a 10-bit product which is passed to accumulator 166a. As illustrated in Figure 4B, accumulator 166a receives the 10-bit product from multiplier 164a, and in combination with the signs of the respective coefficients, accumulates the total of the multiplication products. More specifically, accumulator 166a initially latches the incoming 10-bit product and the 1-bit sign value from multiplexer 168a in latches 170a,b. Because the accumulate requires an 11-bit add operation, the latches are used to allow breaking of the addition operation into two separate add/latch/feedback functions. For example, lower adder 174 first adds the inverted, lower six bits of the incoming value (00010) provided from lower multiplexer 178 thereby producing a rounded 6-bit input value which is then saved in lower latch 176 and the lower six bits of the accumulator. Next, upper adder 182 receives the upper five bits of the input value from latch 180 and adds that to a zero value first received from upper multiplexer 184 and the carryout value received from the uppermost bit of lower latch 176, thereby producing a 5-bit result which is stored in the upper five bits of accumulator latch 186. Once the cycle is completed, it is repeated two more times using the latched adder results from the previous addition cycle to enable the addition/accumulation of the three slow scan filter output values. Subsequent to completing the three accumulation steps, the upper nine bits of the accumulator, the rounded result, is output to the fast scan context buffer, buffer 200a. Similarly, accumulator 166b would be operating concurrently on the outputs of multiplier 164b and multiplexer 168b to accumulate the result for the second slow scan filter. As is apparent from the description of the slow scan filter, and the accompanying accumulator, the afore-described hardware must be suitable for running at or greater than three times the input video rate in order to complete the generation of the filter context for each pixel before a subsequent pixel signal arrives. The multiplying, adding, and accumulating operations inherent in the present filter have been designed to optimize the performance of the filter in just such a situation. Accordingly, the present slow scan filter design has been implemented as part of an application specific integrated circuit, and has been tested for performance at input data rates up to fifteen megahertz. Alternative designs for the slow scan filter are surely possible given a different set of timing constraints. Turning now to Figure 5, once the pixels are filtered with respect to the slow scan context, the resultant slow scan output values are accumulated in respective fast scan context buffers 200a and 200b. The context buffers are arrays of fifteen parallel latches, 204a - 204o and 206a-206o, placed in sequence. These buffers provide the functionality necessary for the individual 9-bit output values to be passed to the fast scan filter, as well as, shifting of the stored values to subsequent latches. For example, a filtered pixel value entering context buffer 200a would first be stored in latch 204a where it would be used as the pix0 input to the fast scan filter of Figure 6. On a subsequent pixel clock, the value of the subject filtered pixel would be transferred from latch 204a to latch 204b, where it would be used as pix1 input to the fast scan filter. Likewise, the subject filtered pixel value would be shifted, on subsequent pixel clocks, through context buffer 200a until it was shifted out the end after latch 204o. Selection of the context passed to fast scan filter 230 is determined by the selection line controlling slow scan multiplexer 208, selecting between the context from slow scan filter 1, 200a, or slow scan filter 2, 200b. The selection line is controlled by the CPU, or other image processing window control, based upon the filtering option desired for the pixel currently being processed. Slow scan multiplexer 208 may also be used to control the selection of the fast scan filter coefficients, including the coefficient signs, in the same manner in which it controls the selection of the filter context. Thus a larger multiplexer may be used to simultaneously select the desired slow scan filter context and their associated fast scan filter coefficients. Referring now to Figure 6, which illustrates the second stage or fast scan filter architecture, fast scan filter 230 initially receives the required slow scan filter output via the multiplexed context buffers 200a or 200b. Initially, fast scan filter 230 pairs the slow scan filter output from symmetric pixels (i.e., pix0 and pix14, or pix3 and pix11) and adds the symmetric values at adders 232a - 232g. Like the slow scan filter, the fast scan filter combines coefficient symmetry along with a 3x speed increase in multiplier speed (each multiplier runs at 3 times the pixel clock rate) to reduce the overall hardware size. Due to this symmetry, terms of like coefficients can be combined to reduce the number of hardware elements. This, coupled with the use of a single fast scan filter saves considerable ASIC die space, and therefore cost, even with the addition of the required multiplexing circuitry. Subsequent to the addition operation, the pixel sums are stored in latches 234a - 234g, respectively. An additional latch, 234h is used to store the value of pix7 , the center value in the slow scan filter context. Another latch is used, latch 234i, to store the actual value of the center or target pixel, which has been moved in sequence with the pix 7 filtered pixel value through the previous filtering operations. The intent of including the buffered center pixel, as well as the Center Pixel Adjust (CPA) coefficient, is to enable their subsequent multiplication and addition to the final filtered result, as done in an enhancement type filter. The fast scan filter coefficients are represented by the letters: D E F G H I J K J I H G F E D and are multiplied by the the associated pixel sums. Considering the pixel values for pix1 and pix13 , for example, the sum of the two values is stored in latch 234b until passed to multiplier 240a via multiplexer 236a on the second of three multiply/accumulate cycles. The sum of pix1 and pix13 is multiplied by coefficient E , provided via coefficient multiplexer 242a, and then stored in latch 244a. Subsequently, the value stored in latch 244a [( pix1 + pix13 )*E] is added to the value stored in latch 244b [( pix4 + pix10 )* H ] by adder 246. The sum at adder 246 is then added to the value of latch 244c [ pix7*K ] at adder 248, the resulting sum being stored in latch 252. In a similar fashion, all of the remaining pixel pairs would be multiplied by their associated coefficients. Subsequent to executing the multiplication and addition operations, as illustrated in Figure 6, the value stored in latch 252 is scaled and checked for overflow in accordance with the scale factor determined for the filter coefficients being used. Scaling depends upon the magnitude of the input coefficients chosen for use in the filter. Briefly, the sum of the absolute value of the slow scan coefficients must be less than or equal to one, and the sum of the absolute value of the fast scan and center pixel adjust coefficients must also be less than or equal to one. If these conditions are initially met, then the scale factor is one. If these conditions are not met, then all coefficients must be divided by 2 or 4 in order to meet the requirements. In essence, the scale factor determines which eight bits of the 10-bit filtered result contained in latch 252 are the final filter output. The selection of the valid bits results in some truncation error, which, given the appropriate input image may be discernible in an output image. However, the noise present in most documents and imaging systems generally allows the truncation error to remain undetected. Overflow checking is required because the filtered result contained in latch 252 is greater than an 8-bit value. Hence, overflow checking ensures that the filter output will be set to the maximum (FF hex) when appropriate, in accordance with the actual filtered result and the coefficient scale factor. In addition, underflow checking is required due to the potential use of negative filter coefficients. The underflow checking ensures that a negative filter result will be output as zero (00 hex). After the scaling, or the selection and truncation operations, the resulting 8-bit filtered pixel value is output. In a typical image processing implementation, one filter may be programmed as a low pass filter to remove screen patterns in halftone originals, while the other filter could be programmed as an edge enhancement filter to improve fine line and character reproduction when thresholding. Operating the two-dimensional filter of the present application in conjunction with the halftone detection capabilities of the image segmentation block described in Figure 1 would then allow the automatic selection of the appropriate filters during the processing of data. Thus, enabling the accurate and automatic processing of image signals generated from original documents having halftone images interspersed within text. In an alternative embodiment, the two-dimensional filter of the present invention may be implemented in software, employing the steps of the afore-described hardware implementation. Referring now to Figure 7, which is a flowchart showing the processing steps used to simulate the two-dimensional filtering operations of the present invention in software, the process begins with initialization step 300. In general, initialization might include the reading of the filter coefficients, allocation of memory in accordance with the size of the filter, opening and establishment of file pointers and additional initialization of variables. For instance, the software embodiment of the two-dimensional filter also builds a look-up table of possible multiplication products for the coefficients input to the system. The look-up table implementation is more efficient for execution of the numerous multiplication steps necessary in the filtering of the digital input image. Continuing at step 302, the system would retrieve the next, or in this case, first, scanline of image data. From this scanline, the system would sequentially process, or filter, each pixel within the line via the get next pixel step, step 304. In order to efficiently process values for more than one two-dimensional filter, the software would also include a filter loop, as controlled by step 306 in conjunction with decision step 324. It should be noted that, as with the hardware embodiment, no filtering is begun until there are sufficient pixels to establish context for both the slow scan and fast scan portions of the filter. More specifically, the "get next filter loop" would execute enclosed steps 308 through 322 for each filter to be run in software. In practice, the use of additional filters will cause an increase in the processing time required to complete the filtering operation. Next, step 308 generates the slow scan filter context using pixel values from five or fewer scanlines, by adding the values of the symmetric pixels which lie in the four scanlines immediately adjacent the scanline currently being processed. Here, as well as in the generation of the fast scan filter context, the multiplication of the coefficient values is most efficiently executed through the use of the multiplication look-up tables which were generated in initialization step 300. Once the context has been established for a target pixel, it is stored in a ring type buffer, step 310. The ring buffer is used as an expedient method of carrying out the operation of the context buffer of Figure 5. After the ring buffer has sufficient context to support the fast scan filter, the process continues at step 312, where the symmetric, or mirror image, pixel pairs are summed, multiplied by their respective fast scan filter coefficients, and accumulated to produce the following result: sum = (pix0 + pix14)*D + (pix1 + pix13)*E + (pix2 + pix12)*F + (pix3 + pix11)*G + (pix4 + pix10)*H + (pix5 + pix9)*l + (pix6 + pix8)*J + pix7*K. As shown in the equation above, the center pixel addition is controlled by the test at step 314. If the filter order is odd, meaning that there is a center pixel, pix7 is multiplied by center pixel coefficient K in step 316. Additionally, as in the hardware embodiment, an adjusted center pixel value may also be added to the accumulated filter sum at this point. Following the accumulation of interim fast scan filter values, the final sum is then scaled at step 318, in accordance with the user selectable scale factor and determined based upon the actual two-dimensional filter coefficient used. Next, the scaled, or shifted, filter result is checked to determine if overflow or underflow conditions exists, at step 320, prior to being stored in step 322. Should an overflow or underflow (negative) filter result be detected, the value stored will be set to the maximum or minimum filter output value, respectively. After storage of the two-dimensional filtered pixel value, test steps 324, 326 and 328 are executed to determine if and where further processing is to be continued. In one embodiment, these test operations may be executed as part of a loop-type control structure. Upon successful completion of the two-dimensional filtering of all pixels within the image, control would be returned to the calling or parent function for further processing, display, or printing of the filtered output image. In recapitulation, the present invention implements a two-dimensional digital filter using two one-dimensional transformations. The two-dimensional filtering method and apparatus of the present invention enable the efficient processing of digital image data, so as to increase processing efficiency and reduce the costs of any associated hardware.

Claims: An image processing device for filtering digital image data, comprising: a plurality of one-dimensional filters operating in a first dimension on the digital image data; means for selecting the output of one of said first dimensional filters; and a single one-dimensional filter operating in a second dimension, the output of the selecting means being supplied to the input of said filter operating in the second dimension. The device of claim 1, wherein: each of the one-dimensional filters operating in the first dimension are adapted to operate on the digital image data in accordance with predetermined filter coefficients to produce a one-dimensional output signal as said output; the single second dimension filter is adapted to receive, in use, the one-dimensional output signal from said selected one first dimension filter and operate on said output signal in accordance with predetermined filter coefficients to produce a second filtered output signal therefrom. A filter device providing a plurality of two dimensional digital filters, comprising: the device of claim 1; wherein said filters operating in the first dimension comprise first stage filters for producing a one-dimensional filtered output signal from an array of input pixel signals; said filter operating in the second dimension comprises a second stage filter, suitable for receiving output signals from said selected first filter and applying a second filtering operation thereto, to produce a two-dimensional filtered output signal; and said selecting means comprises multiplexing means for controlling the selection of the output signals of the first stage filter to be used as the input to the second stage filter. The filter device of claim 3, further comprising means, operating in conjunction with the first and second stage filters and the multiplexing means, for controlling the multiplexer selection of the first stage filter output on a pixel signal by pixel signal basis. The filter device of any of the preceding claims, further comprising a plurality of context buffers, said context buffers storing the output signals from each of the first dimension or first stage filters to enable the second dimension or second stage filter to access the stored output signals in accordance with the selection determined by the control means. The device of any of the preceding claims, further comprising a plurality of digital image data buffers with each digital image buffer being suitable for storing incoming digital image data so as to provide sufficient data context so as to enable the accurate operation of the plurality of one-dimensional filters. An apparatus for implementing a plurality of two-dimensional finite impulse response filters for the processing of a digital image represented as an x-y array of digital data elements, comprising: the device of claim 1; memory means for storing up to n sets of filter coefficients to be applied to the digital data; and means for storing a plurality of sets of output context, one set of output context for each first dimension filter, each context set consisting of a plurality of sequential output values generated by one of the first dimension filters; wherein said first dimension filters are adapted to operate on the digital image data along the y direction, each first dimension filter producing a single output value for each set of digital input values in accordance with one said sets of filter coefficients; wherein the selecting means is operable in conjunction with the first dimension filters for selecting a stored context set and an associated coefficient set; and wherein said second dimension filter is operable along the stored context set to produce a filtered output pixel value in accordance with the selected set of filter coefficients. An apparatus for implementing a plurality of m by n two-dimensional finite impulse response filters for the processing of a digital image represented as an orthogonal array of digital image signals, comprising: the device of claim 1; memory means for storing a plurality of unique sets of filter coefficients to be applied to the digital signals; a plurality of n element wide context buffers for sequentially storing the output signals generated by the first dimension filters, each of the buffers being capable of storing n sequentially generated output values from one of the first dimension filters; means, operating in conjunction with the plurality of first dimension filter context buffers, for reading the stored output signals from a selected context buffer; a plurality of one-dimensional first dimension filters operating on m digital input signals, each of the filters producing a single output signal for each set of digital input signals in accordance with one of the sets of filter coefficients; wherein the selecting means includes means for selecting one of the plurality of first dimension filter context buffers as said selected context buffer, and means. operating in conjunction with said context buffer selecting means, for selecting the coefficient set associated with the context buffer; and wherein said second dimension filter comprises an n element one-dimensional filter operating on the stored context set to produce a filtered output signal in accordance with the selected set of filter coefficients. The device of any of the preceding claims, wherein each of the plurality of first dimension filters includes: means for latching the input digital image data or pixel signals; means for adding symmetric pairs of the latched data values to produce a sum; means for latching the resultant sums of the symmetric pair values; means for multiplying the latched sums by predetermined filter coefficients; and means for accumulating the products output by the multiplying means, to produce an output for the first dimension of first stage filter. The image processing device of claim 9, wherein the multiplying means operates at a rate greater than the incoming data rate, thereby enabling a single multiplication means to sequentially produce all of the multiplication products during a single input data cycle. A method for two-dimensionally filtering digital signals, comprising the steps of: simultaneously inputting to a plurality of one-dimensional first dimension filters operating in a first dimension to digital signals oriented along a first direction, each first dimension filter operating on the digital signals in accordance with a unique set of filter coefficients; selecting, in accordance with the desired filter characteristics, the output of one of said first dimension filters to be used as the input for a subsequent filtering operation; and applying a single one-dimensional second dimension filter operating in a second dimension to the signals at the selected output, the additional second dimension filter operating on said signals in accordance with the unique set of filter coefficients to produce a two-dimensional filtered output.

Inventors: CLINGERMAN TERRI A, WILLIAMS LEON C, CLINGERMAN, TERRI A., WILLIAMS, LEON C.
Applicants: XEROX CORP, XEROX CORPORATION
Application year: 1992
Main classification: H04N1
IPC codes: H03H17, G06F17, G06T5