Error diffusion pattern shifting reduction through programmable threshold perturbation

Abstract: A process eliminates pattern shifting artifacts in a printed image by perturbing a threshold/image signal value relationship when a multi-level grey signal (VIDEO) is binarized. The process utilizes a programmable multi-level grey signal modifying circuit (5) for modifying the multi-level grey signal (VIDEO) by a predetermined value according to its grey level (see Fig.6) The modified multi-level grey signal (VIDEO) is binarized by a comparator (1) to a binary pixel signal according to a relationship between the modified multi-level grey signal (VIDEO) and a threshold value ("128"). The process further generates an error corresponding to the relationship and diffuses the error to neighboring pixels. The multi-level grey signal (VIDEO) is modified with either random noise multiplied by a grey level dependent coefficient or by a predetermined value from a checkerboard or vertical line pattern from a pattern generator (7; Figs. 4,5). The value from the pattern is dependent upon the grey level and pixel location of the image data. An apparatus for implementing the method is also disclosed.

Description: The present invention is directed to a system and method for reducing error diffusion pattern shifting at certain grey levels. More specifically, the present invention is directed to the reduction of error diffusion pattern shifting in certain grey levels by perturbing the threshold value used to binarize the image data. There are many methods of rendering grey images on an output device. One such example is error diffusion. Error diffusion can render complex images that contain a mixture of text and picture reasonably well. The utilization of error diffusion eliminates the need to have image segmentation to separate the text from the picture so that the picture aspect of the document can be screened and the text aspect of the document can be thresholded. Figure 1 illustrates a typical error diffusion binarization circuit. In Figure 1, a modified video signal is fed to a comparator 1 which compares the modified video signal to a threshold value. The comparator 1 outputs a logic one when the modified video signal has a value greater than or equal to the threshold value and outputs a logic zero when the modified video signal has a value less than the threshold value. Depending on whether the rendering device connected to this error diffusion binarization circuit is a write white system or a write black system, the logic value of the output from the comparator 1 will cause the rendering device to produce a pixel or not. In addition to producing the binary value for the rendering device, the comparator 1 produces an error value. The error value is the modified video signal value when the modified video signal has a value less than the threshold value, or the error value is equal to the modified video signal value minus the maximum video value when the modified video signal has a value greater than or equal to the threshold value. The error is diffused to downstream pixels, the next pixel in the same scanline and pixels in the next scanline. This error is then accumulated for each pixel such that when a particular pixel is to be processed by the error diffusion binarization circuit, the accumulated error value for the particular pixel is added to the incoming video signal corresponding to the particular pixel to produce the modified video signal being fed into comparator 1. One problem associated with the utilization of error diffusion in rendering an image on a document is the occurrence of periodically repeating patterns. These patterns occur most notably at the grey levels of 85, 128, and 170 when an 8 bit data word is utilized to represent the grey level of the image data. For example, when the grey level input is 128, the binarized image can alternate between a checkerboard pattern and a vertical line pattern. Depending on the printer spot size and the grey level at which the spot was mapped, the vertical line pattern can appear lighter than the checkered board pattern, thereby producing an undesired artifact. The idea of dithering or adding threshold perturbations to defeat visual artifacts of a regular and deterministic nature has been utilized in the prior art. For example, in the article "Digital Halftoning" by Robert Ulichney, it was proposed to add random noise, across the entire image, to the elements of the error weights or to the threshold to defeat the visual artifacts discussed above. However, by adding noise to all parts of an image tends to degrade the image and will also destroy the dot pattern established in the highlight and shadow areas. Therefore, it is desirable to perturb only the threshold in those areas where the occurrence of periodically repeating patterns are distracting. More specifically, it is desirable to eliminate pattern shifting artifacts by making one of the patterns much less likely to occur. On the other hand, it is desirable to mask this artifact by making the transitions between the patterns happen more frequently, thereby breaking up the regular patterns. EP-A-0544511 relates to a method of half-toning images with enhanced dynamic range and edge enhanced error diffusion. In this case, for grey pixel values where the value of the pixel has one of a relatively large number of input levels, the pixels are directed through an error diffusion quantisation process to convert the value of the pixel to one of a relatively small number of values. EP-A-0507356 relates to bi-level image display signal processing apparatus. The apparatus converts step graduation density values of successive pixel elements into bi-level values for display by a bi-level display device. A bi-level error for each picture element is determined and an appropriate density value for the element is apportioned among a set of periphery adjacent picture elements by computing a corresponding set of error apportionment values. The document PROC. OF THE SID, vol. 25, No. 4, 1984, New York, pages 321-329; H. KOTERA et al.: "A poster-size color ink-jet printing system" describes an ink-jet printing system which directly reproduces poster-size color images. The system obtains 64 grey-levels by a combination of the dot matrix and dot size modulation. Color masking coefficients, including non-linear terms are optimised using the method of at least squares allowing a color correction process to be applied. PROC. OF THE SID, vol. 24, No. 3, 1983, Los Angeles, CA, pages 253-258; C.BILLOTET-HOFFMANN et al.: "On the error diffusion technique for electronic halftoning" describes electronic halftoning using error correction methods in applying the matrix orientated reproduction situation. In accordance with the present invention, we provide a system and corresponding method for processing image data having a multi-level grey signal (VIDEO) having a first number of grey levels, comprising: threshold means for generating a threshold value; conversion means for generating an output having a second number of grey levels based on a relationship between the threshold value and the multi-level grey signal, the second number of grey levels being less than the first number of grey levels; and perturbing means for perturbing the relationship between the threshold value and the multi-level grey signal according to the grey level of the multi-level grey signal, thereby effecting the output from said conversion means, characterised in that the perturbing means adds random noise to (i) the threshold value, or (ii) the multi-level grey signal according to the grey level of the multi-level grey signal. The following is a brief description of each drawing used to describe the present invention, and thus, are being presented for illustrative purpose only and should not be limitative of the scope of the present invention wherein: Figure 1 shows a block diagram illustrating a circuit utilized in the prior art to binarize image data; Figure 2 shows a block diagram illustrating one embodiment of the present invention which perturbs the threshold by adding random noise to the image signal; Figure 3 shows a block diagram illustrating another embodiment of the present invention which adds random noise to perturb the threshold; Figure 4 shows a block diagram illustrating a noise generator utilized in the preferred embodiments of the present invention; Figure 5 shows a flowchart illustrating the perturbing of the threshold according to the concepts of the present invention; Figure 6 shows a flowchart illustrating the adding of random noise to the image signal to perturb the threshold according to the concepts of the present invention; Figure 7 shows a flowchart illustrating the addition of random noise to the threshold signal to perturb the threshold relationship according to the concepts of the present invention; Figure 8 shows a pixel representation illustrating the artifact of periodically repeating checkerboard and vertical line patterns in a particular grey level image region; Figure 9 shows a pixel representation of a certain grey level without threshold permutation; Figure 10 shows a pixel representation illustrating the results of performing threshold permutation on the image of Figure 9 ; and Figure 11 illustrates a graph showing a preferred relationship between the noise amplitude coefficients and the grey level values of the video signal. Figure 2 illustrates one embodiment of the present invention which perturbs a threshold relationship between a modified video image signal ("VIDEO") and a threshold signal ("128") by adding random noise to an error diffusion modified video or image signal in an error diffusion binarization system. In Figure 2, a random noise generator 5 produces a random noise signal which is added to the error diffusion modified image signal by adder 3. The random noise produced by the noise generator 5 is a function of the grey level of the image to be thresholded. More specifically, in the preferred embodiment of the present invention, if the grey level to be threshold represent either 128, 85, or 64, when utilizing an 8 bit data word to represent a grey level of the image data, the random noise generator 5 will produce some random noise level which will be added to the image or video signal. It is noted that these selected grey levels correspond to the preferred embodiment of the present invention, but any other desired grey level can be utilized to trigger the generation of the random noise to be added to the image or video signal. The modified video or image signal outputted by the adder 3 is then binarized by comparator circuit 1. The comparator circuit 1 compares the modified video or image signal with a threshold value, which in the preferred embodiment is 128. If the modified video or image signal is greater than or equal to 128, the comparator outputs a logical value of 1 indicating that the pixel is ON or if the modified video or image signal is less than 128, the comparator circuit 1 output a logical 0 representing that the pixel is OFF. An error is generated from this binarization process wherein this error is diffused to adjacent pixels utilizing any conventional error diffusion process. In the preferred embodiment of the present invention, the error diffusion process is the processes disclosed co-pending US patent applications, Numbers 95 305 328.7; 95 305 325.3; and 95 305 324.6, a copy of which was filed with the present application. It is noted that the video signal entering the adder 3 is initially modified to include any error diffused to that pixel from previous binarization processes. Figure 3 illustrates a variation of the embodiment of the present invention illustrated in Figure 2. In this embodiment, the present invention perturbs a threshold relationship between an error diffusion modified video image signal ("VIDEO") and a threshold signal ("128") by adding random noise to the threshold signal. In Figure 3, a random noise generator 5 produces a random noise signal which is added to the threshold signal by adder 3. The random noise produced by the noise generator 5 is a function of the grey level of the image to be threshold. The remaining aspects or function illustrated by Figure 3 are the same as those described above with respect to Figure 2. Figure 4 illustrates a random noise generator as utilized in the preferred embodiment of the present invention. The random noise generator circuit 5 includes a random noise generator 11 which produces a random noise signal which is fed to a multiplier 15. In the preferred embodiment, the random number generated by the random noise generator 11 is uniformly distributed between plus or minus 255 with a period of over 14 million. The noise generator circuit 5 also includes a noise look-up table 13 which outputs a coefficient corresponding to the grey level information received by the look-up table. For example, in the preferred embodiment of the present invention, if the inputted grey level is 128 on an 8 bit scale, the coefficient generated by the noise look-up table is 1. On the other hand, if the grey value is 85, the coefficient generated by the noise look-up table is 0.5. In other words, each grey value has assigned thereto a coefficient. The coefficient can be a value as low as 1/256. The look-up table 13 programs or tailors the amplitude of the random noise added to the threshold or image signal as a function of the input grey level. The noise look-up table 13 holds N-bit fraction numbers, coefficients, (as a function of input grey levels) which are multiplied with the random noise (number) generated by the random noise generator 11 and later added to the threshold or image signal value. Any noise profile can be loaded into the look-up table to selectively vary the location and magnitude of the threshold permutation in order to disrupt the periodicity of any objectional pattern. A preferred pattern or relationship is illustrated in Figure 11 In Figure 11 the graph shows the relationship between the noise coefficients and the grey level values. For example, in one embodiment, the noise amplitude coefficient at grey level value 128 is 0.375 and the noise amplitude coefficients at grey level values 64 and 192 are 0.125. These values can be adjusted to reflect the particular properties of the printing device. Moreover, the pattern is not limited to a three peak pattern. The pattern may have any multitude of peaks. The coefficient from the look-up table 13 is fed to the multiplier 15 which multiplies the coefficient and the noise signal generated by the random noise generator 11. The product of this multiplication is the actual random noise signal fed to the adders 3 in Figures 2 and 3. Figure 5 illustrates the general conceptual method utilized by the present invention to perturb the threshold relationship at certain grey levels. As illustrated in Figure 7, at Step S1, it is determined whether the grey level of the image to be threshold is equal to 1/4, 1/3, or 1/2 (corresponding to 64,85 and 128). If the image data is equal to one of these grey levels, the threshold/signal relationship is perturbed at Step S2. After the threshold signal relationship has been perturbed at Step S2 or if the image data has a grey level not equal to 1/4, 1/3, or 1/2, it is determined whether the video signal is greater than or equal to the threshold value at Step S3. If the video signal is greater than or equal to the threshold value, Step S4 sets the pixel value to be ON and Step S5 calculates the error to be utilized in the error diffusion process. However, if the video signal is less than the threshold value, Step S6 sets the pixel value to be OFF and the error is calculated in Step S7 to be utilized in the error diffusion process. After calculating the error in Step S5 or S7, the process distributes the error to downstream pixels in Step S8. Figure 6 illustrates a particular method utilized by the present invention to perturb the threshold relationship at certain grey levels. As illustrated in Figure 6, at Step S1, it is determined whether the grey level of the image to be threshold is equal to 1/4, 1/3, or 1/2. If the image data is equal to one of these grey levels, random noise is added to the video signal to perturb the threshold/image signal relationship at Step S21. After the threshold signal relationship has been perturbed at Step S21 or if the image data has a grey level not equal to 1/4, 1/3, or 1/2, it is determined whether the video signal is greater than or equal to the threshold value at Step S3. The remaining steps are the same as described above with respect to Figure 5. Figure 7 illustrates another method utilized by the present invention to perturb the threshold relationship at certain grey levels. As illustrated in Figure 7, at Step S1, it is determined whether the grey level of the image to be threshold is equal to 1/4, 1/3, or 1/2. If the image data is equal to one of these grey levels, random noise is added to the threshold signal to perturb the threshold/image signal relationship at Step S22. After the threshold signal relationship has been perturbed at Step S22 or if the image data has a grey level not equal to 1/4, 1/3, or 1/2, it is determined whether the video signal is greater than or equal to the threshold value at Step S3. The remaining steps are the same as described above with respect to Figure 7. It is noted that although the methods illustrated in Figures 5, 6 and 7 show Step S1 making a determination with respect to three grey level values, Step S1 can be modified from a three value decision state to a state making a determination as to what is the actual the grey level value of the image signal. With this modification, the branch from Step S1 directly to Step S3 is eliminated, and Steps S2, S21, S22, S23, and S24 perturb the threshold/signal relationship for every pixel with a different value. In this way, the threshold/signal relationship is perturbed over the entire image wherein each possible grey level has assigned thereto an individual coefficient value as in Figures 6 and 7. At midtone regions in an image, the possible periodic patterns for equal numbers of white and black pixels are checkerboard, vertical lines, or horizontal lines. Conventionally, the images are left to settle into one of these stages, depending of the weighting coefficients and the boundary conditions of the image processing operation. From a symmetric point of view, however, if the threshold in the error diffusion process is perturbed in a particular manner, the output from the thresholding process would be able to lock into a particular binary output having a certain state. This locking in result would effect the final appearance of the image by reducing the pattern shifting artifacts discussed above. Figure 8 illustrates a pattern shifting artifact occurring at a grey level corresponding to 1/2 (or 128) when the image signal is represented by an eight bit byte. It is noted that in the section corresponding to 121, the pattern is one of vertical lines, whereas the pattern in section 122 is a checkerboard pattern. Moreover, as the image proceeds to section 123, the pattern shifts back to a vertical line pattern. It is this pattern shifting in the midtone region (a region having a grey value of 128 out of a possible 255) that creates the pattern shifting artifact that can be distracting to the actual appearance of the image. It is noted that the shaded squares in Figure 8 represent black pixels in the image to be reproduced and the non-shaded squares in Figure 8 represent white pixels in the image to be reproduced. This convention is also used in Figures 9, 10 and 11. If the present invention is utilized in a color apparatus, the shaded squares in Figure 8 would represent to be printed pixels for a particular color (toner or ink) and the non-shaded squares in Figure 8 would represent not to be printed pixels for a particular color (toner or ink). Figure 9 illustrates a pixel representation of another pattern shifting artifact in a midtone region (a grey level corresponding to 128 or 1/2 for an eight bit image data byte). In Figure 9, section 170 represents an area where a predominant horizontal line pattern is found. Moreover, section 270 also represents an area having a predominant horizontal line pattern. Thus, it is noted that the pattern shifts from a horizontal line pattern in section 170 to a checkerboard pattern then back to a horizontal line pattern in 270 as one travels in a fast scan direction. This pattern shifting artifact is substantially reduced in Figure 10. In Figure 10, the midtone region (128 or 1/2 grey level) is rendered by perturbing the threshold/signal relationship with the inclusion of random noise. In the rendering of the image, the horizontal line patterns are restricted to the areas where sections 171 and 172 overlap section 170 or the areas which correspond to the overlapping of section 270 with sections 271, 272, and 273. The addition of random noise for a particular grey level enables the image to be rendered with a substantial reduction in the pattern shifting artifact. An additional benefit of allowing both the location and the intensity of the threshold relationship perturbation to be programmable is a flexibility to properly apply the correct amount of perturbing noise to any type of preprocessed image prior to applying error diffusion. Preprocessing operations include tonal reproduction curve (TRC) input mapping, gain and offset adjustment, spot overlap compensation, etc. These preprocessing operations all tend to shift objectional periodic patterns to input grey level location other than what has been conventionally expected. Moreover, the noise look-up table can be uniquely programmed and optimized to render images with good quality corresponding to any of the situations described above. More specifically, if the image is preprocessed utilizing a TRC input mapping and gain and offset adjustment, the artifact of pattern shifting can be centered at an input grey level of around 220 Thus, knowing that the pattern shifting artifact has been centered at a different input grey level, the noise look-up table can be programmed to inject random noise into the threshold/video signal relationship when the image signal is at a grey level around the new pattern shifting grey level. Thus, the programmability of the noise look-up table allows the present invention to be readily adaptable to any printing situation. It will be appreciated that various modifications can be implemented. For example, the preferred embodiment of the present invention has been described with respect to a binary printing system; however, this perturbing system can be applied to any situation where multibit image data byte is to be reduced or converted to an image data byte having less bits. Moreover, the perturbation method of the present invention can be readily implemented on an appalication specific integrated circuit (ASIC), thereby enabling the placement of this process in a scanner, electronic subsystem, printer, or display device. Moreover, the present invention has been described with respect to a video range of 0 to 255. However, it is contemplated by the present invention that the video range can be any suitable range to describe the grey level of the pixel being processed. Furthermore, the present invention is readily applicable to any rendering system, not necessarily a binary output device. It is contemplated that the concepts of the present invention are readily applicable to a four-level image output terminal or higher. Lastly, the present invention has been described with respect to a monochrome or black/white environment. However, the concepts of the present invention are readily applicable to a color environment. Namely, the perturbation process of the present invention can be applied to each color space value representing the color pixel. In recapitulation, the present invention provides a process for eliminating pattern shifting artifacts by perturbing the threshold/image signal relationship. The perturbation is based on the grey value of the image data and/or the pixel location of the image data. Moreover, the perturbation is programmable allowing flexibility and adaptability to any situation.

Claims: A system for processing image data having a multi-level grey signal (VIDEO) having a first number of grey levels, comprising: threshold means for generating a threshold value ("128"); conversion means (1) for generating an output having a second number of grey levels based on a relationship between the threshold value and the multi-level grey signal, the second number of grey levels being less than the first number of grey levels; and perturbing means (3,5) for perturbing the relationship between the threshold value and the multi-level grey signal according to the grey level of the multi-level grey signal, thereby effecting the output from said conversion means, characterised in that the perturbing means adds random noise to (i) the threshold value, or (ii) the multi-level grey signal according to the grey level of the multi-level grey signal. The system as claimed in claim 1, wherein said perturbing means perturbs the relationship when the grey level is (i) ½, (ii) ¼, and/or (iii) 1/3, and/or administers a distinct perturbation to the relationship for each grey level. A system according to claim 1 or claim 2, the system further comprising: image means for generating image data having a multi-level grey signal (VIDEO) and wherein the conversion means (1) outputs a binary pixel value according to a relationship between a modified multi-level grey signal from said perturbing means and a threshold value ("128"), generates an error corresponding to the relationship, and diffuses the error to neighbouring pixels. A method of processing image data having a multi-level grey signal having a first number of grey levels, comprising the steps of: (a) generating a threshold value; (b) generating an output having a second number of grey levels based on a relationship between the threshold value and the multi-level grey signal, the second number of grey levels being less than the first number of grey levels; and (c) perturbing the relationship between the threshold value and the multi-level grey signal according to the grey level of the multi-level grey signal, thereby effecting the output of said step (b), characterised in that the method further comprises perturbing the relationship by adding random noise to (i) the threshold value or (ii) the multilevel grey signal according to the grey level of multi-level grey signal.

Inventors: METCALFE DAVID J, SHIAU JENG-NAN, WILLIAMS LEON C, METCALFE, DAVID J., SHIAU, JENG-NAN, WILLIAMS, LEON C.
Applicants: XEROX CORP, XEROX CORPORATION
Application year: 1995
Main classification: H04N1
IPC codes: H04N1, G06T5