Image processing method and apparatus

Abstract: An image processing method and apparatus for effecting a density conversion, using a predetermined density conversion curve, of density data obtained by reading an original having consecutive tones, and a smoothing space filtering process for the density data resulting from the density conversion. The smoothing space filtering process is effected selectively only for density data resulting from the density conversion and belonging to density areas having absolute values of differential coefficients of the density conversion curve exceeding a predetermined value. A random number is added to smoothed density data of a subject pixel. This random number has an amplitude variable with an absolute value of a differential coefficient at a point on the density conversion curve corresponding to the density data of the subject pixel and/or with a standard deviation of density data of pixels in a small area to be subjected to the filtering process.

Description: BACKGROUND OF THE INVENTION (1) Field of the Invention The present invention relates to a method of and an apparatus for effecting a density conversion, using a predetermined density conversion curve, of density data obtained by reading an original having consecutive tones with a prepress scanner or the like, and a smoothing space filtering process for the density data resulting from the density conversion. More particularly, the invention relates to a technique of reducing tone jumps and false contours appearing in an outputted image when the density data are converted digitally. (2) Description of the Related Art A known method of converting density data in a digital process uses a lookup table. Specifically, image signals obtained by reading an original having consecutive tones with a prepress scanner are converted into digital density data of 256 tones, for example. These density data are applied as addresses in the lookup table. The lookup table stores a selected density conversion curve representing output density levels for the respective addresses. Output density levels corresponding to input density levels are read from the lookup table to effect the density conversion of the density data. Fig. 1 is a schematic view of a density conversion curve stored in such a lookup table. In Fig. 1, the horizontal axis represents input density levels and the vertical axis output density levels, both expressed digitally in 256 tones in dot%. Consequently, even though the operator sets a density conversion curve having a smooth characteristic A, the density conversion curve actually stored in the lookup table has a stepwise characteristic B. As seen from the characteristic B in Fig. 1, a large difference occurs in adjacent output density levels in sections where the density conversion curve shows steep gradients (sections C and D in Fig. 1). This results in the inconvenience that the portions of an outputted image corresponding to these sections have low image quality with discontinuity of tone variations (so-called tone jumps) and false contours. In order to reduce the tone jumps and false contours, abrupt changes in the tone are suppressed in conventional practice by effecting a smoothing space filtering process for the output density data resulting from the density conversion. However, such conventional practice has the following disadvantage. According to the prior art, the smoothing space filtering process is effected for the output density data in all sections of the conversion curve. This filtering process, therefore, smooths also the output density data in sections where the density conversion characteristic describes relatively gentle gradients (e.g. section E in Fig. 1). Even the contours in such sections that require density differences are smoothed, thereby blurring the outputted image as a whole. Further, as shown in Fig. 2, sharp boundaries between density levels may be present in the density-converted data. If the smoothing space filtering process is simply effected for such boundaries, curves showing equal density levels will appear in stripes in the boundaries as indicated by arrows in Fig. 3, resulting in an unnatural image. SUMMARY OF THE INVENTION The present invention has been made having regard to the state of the art noted above, and its primary object is to provide an image processing method and apparatus capable of effecting a smoothing space filtering process only for areas prone to tone jumps and false contours. Another object of the present invention is to provide an image processing method and apparatus which prevent stripes from appearing in boundaries between different density levels when a smoothing space filtering process is effected for output density data resulting from a density conversion. The above objects are fulfilled, according to the present invention, by an image processing method according to claim 1. According to the present invention, the smoothing space filtering process is effected only for density data resulting from the density conversion and belonging to density areas having absolute values of differential coefficients of the density conversion curve exceeding a predetermined value. That is, the smoothing space filtering process is effected selectively and only for areas having large density conversion factors and prone to tone jumps and false contours. Consequently, image quality is improved as a whole, with tone jumps and false contours in such areas being suppressed while the other areas are free from blurs due to the smoothing process. The image processing method according to the present invention may further comprise a step of adding a random number to smoothed density data of a subject pixel resulting from the smoothing space filtering process effected at the fifth step. This random number has an amplitude variable with an absolute value of a differential coefficient at a point on the density conversion curve corresponding to the density data of the subject pixel and/or with a standard deviation of density data of pixels in a small area to be subjected to the filtering process. Where the random number added to the smoothed density data has an amplitude variable with an absolute value of a differential coefficient at a point on the density conversion curve corresponding to the density data of the subject pixel, a random number with a large amplitude is added for an area having a density difference enlarged by the density conversion. This reduces the unpleasant stripes resulting from the smoothing process. For an area having a density difference little enlarged, the random number (noise) added has a reduced level to avoid deterioration in image quality. Where the random number added to the smoothed density data has an amplitude variable with a standard deviation of density data of pixels in a small area to be subjected to the filtering process, a random number with a relatively large amplitude is added to smoothed density data of a small area subjected to the smoothing space filtering process and having dispersed density data, i.e. a boundary between different density levels. This is effective to reduce generation of unpleasant stripes due to the smoothing process. The random number (noise) added for an area of little density difference has a reduced level to avoid deterioration in image quality. BRIEF DESCRIPTION OF THE DRAWINGS For the purpose of illustrating the invention, there are shown in the drawings several forms which are presently preferred, it being understood, however, that the invention is not limited to the precise arrangements and instrumentalities shown. Figs. 1 through 3 show the prior art, in which:- Fig. 1 is an explanatory view of a density conversion curve, Fig. 2 is a view showing boundaries between different densities in density data following a density conversion, and Fig. 3 is a view showing a way in which stripes appear as a result of a simple smoothing space filtering process. Figs. 4 through 17 show embodiments of the present invention, in which:- Fig. 4 is a block diagram showing an outline of an image processing apparatus, Fig. 5 is a flowchart of entire density conversion and smoothing image processing, Fig. 6 is a flowchart showing details of a step of designating a density conversion curve, Fig. 7 is a flowchart showing details of a density conversion process, Fig. 8 is a flowchart showing details of a process of calculating absolute values of differential coefficients of the density conversion curve, Fig. 9 is a flowchart showing details of a process of designating sections of the density conversion curve, Fig. 10 is a flowchart showing details of an area map preparation process, Fig. 11 is a flowchart showing details of a smoothing space filtering process, Fig. 12 is a flowchart showing a portion of processing characteristic of a second embodiment, Fig. 13 is a flowchart showing details of a random number generation process in the second embodiment, Figs. 14A through 14C are waveform diagrams illustrating a processing sequence for designating sections of the density conversion curve, Fig. 15 is a schematic view of the area map, Fig. 16 is a schematic view of a small area including a pixel undergoing the smoothing space filtering process, and Fig. 17 is a view illustrating functions of the smoothing space filtering process in the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the present invention will be described in detail hereinafter with reference to the drawings. First Embodiment Fig. 4 is a block diagram showing an outline of an image processing apparatus in a first embodiment of the present invention. Referring to Fig. 4, this apparatus includes a CPU 1 for carrying out various image processing as described later, an input scanner 2, an original image file 3 for storing density data of an original image read by the input scanner 2, an intermediate image file 4 for storing density data of the original image after a density conversion, a processed image file 5 for storing density data resulting from a smoothing space filtering process effected for the density-converted data, an output scanner 6 for recording the density data stored in the processed data file 5 on a photosensitive material, a color display 7 for presenting the original image and other information, a command display 8 for presenting numeric values and other selected conditions, a digitalizer 9 for setting a density conversion curve and other image processing conditions, a lookup table 10 for storing the density conversion curve, a differential coefficient file 11 for storing absolute values of differential coefficients of the density conversion curve, an area designation table 12 for designating density areas in which the absolute values of the differential coefficients of the density conversion curve exceed a predetermined value, and an area map 13 for storing a distribution of areas of the original image whose density data correspond to the density areas set to the area designation table 12. An image processing operation of this apparatus will be described next with reference to the flowchart shown in Fig. 5. First, an original image is read by the input scanner 2 and its density data are stored in the original image file 3 (step S1). The original image is presented on the color display 7 (step 2). At step S3, the operator designates a density conversion curve through the digitalizer 9 while looking at the color display 7 for confirmation. Specifically, as shown in Fig. 6, the color display 7 presents a coordinate system for comparing input density levels (density levels of the original image) and output density levels (density levels after the density conversion) (step S31). The operator inputs, through the digitalizer 9, parameters defining a density conversion curve (step S32). The density conversion curve based on these parameters appears in the coordinate system on the color display 7, and this density conversion curve is set to the lookup table 10 (step S33). Fig. 14A shows an example of density conversion curve set at this time. At step S4, the original image data stored in the original image file 3 is subjected to a density conversion based on the density conversion curve stored in the lookup table 10. Specifically, as shown in Fig. 7, a density data of a pixel to be processed is picked up from the original image data stored in the original image file 3 (step S41). This density data is applied as an input address to the lookup table 10 to read a corresponding output density level therefrom (step S42). The converted density data is stored in the position of the intermediate image file 4 corresponding to the pixel under processing (step S43). The above density conversion is carried out for all the pixels in the original image file 3, and the results are stored in the intermediate image file 4 (step S44). Step S5 is executed to determine absolute values of the differential coefficients of the density conversion curve set to the lookup table 10. Specifically, as shown in Fig. 8, the output density data is read from the lookup table 10 for each stage of the input density data (step S51). This density data is compared with the density data of an adjacent input density stage, and the greater of the two absolute values is stored in the differential coefficient file 11 as a differential coefficient of the density conversion curve for this stage of density data (step S52). This above process is repeated for all the 256 stages (step S53). Fig. 14B shows the absolute values of the differential coefficients of the density conversion curve stored in the differential coefficient file 11. Step S6 is executed to extract sections of the curve in which the differential coefficients obtained as above exceed a predetermined value, and to set such sections to the area designation table 12. Specifically, as shown in Fig. 9, the absolute value of the differential coefficient of the density conversion curve for one stage of the density data is read from the differential coefficient file 11 (step S61). If this absolute value is 2 or more, for example, the value of this density data is set to "1" in the area designation table 12, and otherwise the value is set to "0" (step S62). This area designation process is repeated for the absolute values of the differential coefficients of all the 256 stages (step S63). Fig. 14C is a schematic view of the resulting area designation table 12. Step S7 is executed to set to the area map 13 the areas of the density data in the original image file 3 to be smoothed on the basis of the data in the area designation table 12. Specifically, as shown in Fig. 10, the density data of a pixel to be smoothed is read from the original image file 3 (step S71). If the value of this density data corresponds to area "1" in the area designation table 12, "1" is set to the corresponding position in the area map 13, and otherwise "0" is set thereto (step S72). The above area setting is repeated for all the pixels in the original image (step S73). Fig. 15 shows the area map 13 obtained from the above process. The hatched portions of Fig. 15 are the areas to be smoothed to which "1" has been set, and the other portions are areas requiring no smoothing operation to which "0" has been set. The broken lines show contours in the original image. At step S8, the density data of a small area with a pixel to be smoothed lying in the center (in this example, a total of 9 pixels, i.e. 3 by 3, with a pixel to be smoothed lying in the center) are extracted from each portion corresponding to area "1" set to the area map 13 among density-converted data stored in the intermediate image file 4. Then, step S9 is executed to obtain an average value of the density data of the small area of 3 by 3 pixels including the pixel to be smoothed which are read from the intermediate image file 4, and to store the average value in a corresponding position in the processed image file 5 as density data of the smoothed pixel. Specifically, as shown in Fig. 11, the density data of a small area (3x3 pixels) centering around a pixel to be smoothed are read from the intermediate image file 4 (step S91). An average value is derived in a floating-point real number from these density data (step S92). The density data obtained in a real number is converted to an integer (i.e. quantized) and stored in the position of the processed image file 5 corresponding to the subject pixel (step S93). Where the pixels surrounding the subject pixel r x,y are expressed as shown in Fig. 16, the density data Qxy of the smoothed image in the small area including the subject pixel r x,y is expressed by the following equation: After repeating the processes at steps S8 and S9 for all the pixels in the subject areas in the area map 13 (step S10), the smoothed density data in the processed image file 5 are outputted to the output scanner (step S11). In this embodiment, as described above, the smoothing space filtering process is effected only for the density areas in which the absolute values of differential coefficients of the density conversion curve are "2" or more, i.e. the input density data are enlarged twofold or more. This process reduces tone jumps and false contours appearing in areas having large density conversion factors. Since no smoothing space filtering process is applied to areas having small density conversion factors, these areas are free from blurred contours. Second Embodiment The characteristic feature of this embodiment lies in a process of adding a random number to the density data resulting from the smoothing space filtering process effected for a density area in which the input density data are enlarged twofold or more. In particular, the random number has an amplitude varied with a standard deviation in the small area including a subject pixel and with the differential coefficient of the density conversion curve. This method is executed with the same apparatus as in the first embodiment shown in Fig. 4, and will not be described again. The second embodiment will be described hereinafter with reference to the flowchart shown in Fig. 12. Step S12 in Fig. 12 follows steps S1 through S8 of the first embodiment shown in Fig. 5, i.e. follows extraction of the density data of a small area with a pixel to be smoothed from a portion in the intermediate image file 4 corresponding to area "1" set to the area map 13. Step S12 is executed to obtain a value of standard deviation of each density data in the small area extracted at step S8. Where the pixels surrounding the subject pixel r x,y are expressed as shown in Fig. 16, the standard deviation Sxy in the small area including the subject pixel r x,y is derived from the following equation: At step S13, a random number is generated on the basis of the standard deviation obtained at step S12 and the absolute value of a differential coefficient of the density conversion curve stored in the differential coefficient file 11. Specifically, as shown in Fig. 13, the density data of the subject pixel is read from the original image file 3 (step S131). Then, the absolute value of the differential coefficient of the density conversion curve for this density data is read from the differential coefficient file 11 (step S132). A range of random number generation is determined from the standard deviation Sxy of this small area and the absolute value |f'(P x,y)| of the differential coefficient (step S133). A uniform random number is generated in a floating-point real number for that range (step S134). At step S14, an average value of the density data of the small area of 3 by 3 pixels including the pixel to be smoothed which are read from the intermediate image file 4 is obtained as described in the first embodiment, and this average value is stored in a corresponding position in the processed image file 5 as density data of the smoothed pixel. Specifically, the density data of a small area (3x3 pixels) centering around a pixel to be smoothed are read from the intermediate image file 4. An average value is derived in a floating-point real number from these density data. This average value and the random number generated at step S13 are added to obtain a density data of the subject pixel in a real number. The density data thus obtained is converted to an integer (i.e. quantized) and stored in the position of the processed image file 5 corresponding to the subject pixel. The resulting density data Qxy of the smoothed image is expressed by the following equation: In the above equation, md is a random number generated in the range of -1 to +1 (which corresponds to a random number generated at a uniform rate, known as a white random number), and α is a constant appropriately selected to adjust the effect of the random number (e.g. varied degrees of roughness) in accordance with degrees of density variations. In this embodiment, the amplitude of the random number is varied using both the standard deviation of the small area centering around the subject pixel and the absolute value of the differential coefficient of the density conversion curve. However, only one of these values may be used in varying the amplitude of the random number. Where, for example, only the absolute value of the differential coefficient of the density conversion curve is used in varying the amplitude of the random number, the density data Qxy of the smoothed image is expressed by the following equation: Where only the standard deviation of the small area centering around the subject pixel is used in varying the amplitude of the random number, the density data Qxy of the smoothed image is expressed by the following equation: After step S14, the operation proceeds to step S10 in Fig. 5, to carry out the above smoothing process for all the pixels in the subject areas in the area map 13. Thereafter the smoothed density data in the processed image file 5 are outputted to the output scanner. In the smoothing space filtering process of this embodiment, as described above, the amplitude of the random number added to the average density value in the small area centering around a subject pixel resulting from the smoothing process is varied in accordance with the standard deviation of the small area and with the absolute value of the differential coefficient of the density conversion curve. In this way, random numbers with large amplitudes are added for those density data resulting from the density conversion and having large density differences. Consequently, as shown in Fig. 17, the density levels are dispersed around boundaries having large density differences, thereby reducing generation of density stripes due to the smoothing process. Besides, the random numbers have reduced amplitudes for areas of little density difference, to produce a low-noise image and to improve image quality as a whole. Each of the foregoing embodiments employs the process of smoothing the density data of a subject pixel by calculating the average value of the density data of the small, 3x3 pixel area centering around the subject pixel. However, the method of executing the smoothing space filtering process is variable and not limited to the method described in the embodiments. The present invention may be embodied in other specific forms without departing from the scope of the invention as defined by the appended claims.

Claims: An image processing method for effecting a density conversion, using a predetermined density conversion curve, of density data obtained by reading an original having consecutive tones, and a smoothing space filtering process for the density data resulting from the density conversion, said method comprising: a first step of effecting the density conversion, based on the predetermined density conversion curve, of density data of an original image; a second step of obtaining the absolute value of the differential coefficient for each point on said density conversion curve; a third step of determining for which points on said curve said absolute values exceed a predetermined value; a fourth step of preparing a map of density data of the original image corresponding to the points found in the third step; and a fifth step of effecting the smoothing space filtering process for density-converted data belonging to said map prepared at the fourth step. An image processing method as defined in claim 1, further comprising a step of adding a random number to smoothed density data of a subject pixel resulting from said smoothing space filtering process effected at the fifth step, said random number having an amplitude variable with an absolute value of a differential coefficient at a point on said density conversion curve corresponding to the density data of said subject pixel. An image processing method as defined in claim 1, further comprising a step of adding a random number to smoothed density data of a subject pixel resulting from said smoothing space filtering process effected at the fifth step, said random number having an amplitude variable with a standard deviation of density data of pixels in a small area to be subjected to said filtering process. An image processing method as defined in claim 1, further comprising a step of adding a random number to smoothed density data of a subject pixel resulting from said smoothing space filtering process effected at the fifth step, said random number having an amplitude variable with an absolute value of a differential coefficient at a point on said density conversion curve corresponding to the density data of said subject pixel and with a standard deviation of density data of pixels in a small area to be subjected to said filtering process. An image processing apparatus for effecting a density conversion, using a predetermined density conversion curve, of density data obtained by reading an original having consecutive tones, and a smoothing space filtering process for the density data resulting from the density conversion, said apparatus comprising: input means for reading the original; original image storage means (3) for storing density data of an original image read by said input means; designating means for designating a density conversion curve of the density data of said original image; density conversion curve storage means (10) for storing said density conversion curve designated by said designating means; density conversion means for effecting a density conversion, based on said density conversion curve stored in said density conversion curve storage means, of the density data of said original image in said original image storage means; intermediate image storage means (4) for storing density data resulting from the density conversion by said density conversion means; differential coefficient calculating means (1) for calculating absolute values of differential coefficients of points on said density conversion curve stored in said density conversion curve storage means; density area extracting means for determining for which points on said curve said absolute values exceed a predetermined value; density area storage means for storing the points found by said density area extracting means; determining means for referring to contents of said density area storage means and determining whether the density data of pixels successively read from said original image storage means correspond to the conversion curve points stored in said density area storage means; area map storage means for storing a map of results provided by said determining means; smoothing means for successively reading the density data of pixels from said intermediate image storage means, outputting the density data after effecting the smoothing space filtering process therefor when said pixels belong to a subject area stored in said area map storage means, and outputting the density data without effecting the smoothing space filtering process when said pixels are outside said subject area; processed image storage means for storing the density data of said pixels successively outputted from said smoothing means; and output means for outputting contents of said processed image storage means. An image processing apparatus as defined in claim 5, further comprising first operating means for adding a random number to smoothed density data of a subject pixel resulting from said smoothing space filtering process, said random number having an amplitude variable with an absolute value of a differential coefficient at a point on said density conversion curve corresponding to the density data of said subject pixel, and outputting a resulting sum to said processed image storage means. An image processing apparatus as defined in claim 5, further comprising second operating means for adding a random number to smoothed density data of a subject pixel resulting from said smoothing space filtering process, said random number having an amplitude variable with a standard deviation of density data of pixels in a small area to be subjected to said filtering process, and outputting a resulting sum to said processed image storage means. An image processing apparatus as defined in claim 5, further comprising third operating means for adding a random number to smoothed density data of a subject pixel resulting from said smoothing space filtering process, said random number having an amplitude variable with an absolute value of a differential coefficient at a point on said density conversion curve corresponding to the density data of said subject pixel and with a standard deviation of density data of pixels in a small area to be subjected to said filtering process, and outputting a resulting sum to said processed image storage means.

Inventors: IKEDA IWATA, IKEDA, IWATA, Ikeda, Iwata, c/o Dainippon Screen Mfg. Co., Ltd.
Applicants: DAINIPPON SCREEN MFG, DAINIPPON SCREEN MFG. CO., LTD.
Application year: 1991
Main classification: H04N1
IPC codes: H04N1