JP2007102730A - Image correction device, image correction program and image correction method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image correction device for easily removing any noise from an image expressed by pixel data. <P>SOLUTION: A scanning pat 52 successively scans each of the pixels of an image based on binary imaged data Din1 for one screen stored in a frame memory 51. Also, an arithmetic part 53 and a setting part 54 perform noise removal processing to each pixel so that the result of noise removal processing to scanned pixels can be reflected on noise removal processing to the next scanning object pixels. Thus, it is possible to remove a noise only by scanning the whole image once. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image correction apparatus, an image correction program, and an image correction method for removing noise from an image expressed by pixel data.

  Conventionally, various techniques have been disclosed as methods for removing noise from an image expressed by a plurality of pixel data. For example, in Patent Document 1, whether or not the pixel of interest is noise depends on whether or not the pattern of the pixel of interest and its neighboring 8 pixels match the registered reference pattern for an image composed of a binarized video signal. A noise removal method for determining whether or not is disclosed.

  Further, in Patent Document 2, regarding the binarized image data, the pixel of interest is determined by whether or not the pixel of interest and a 3 × 3 pattern of the 8 pixels in the vicinity match the registered mask pattern. A noise removal method is disclosed in which vertical line (line) noise is removed by determining whether or not the above is true.

Japanese Patent Laid-Open No. 7-160872 JP-A-8-272756

  However, in these noise removal methods, it is necessary to scan the entire image many times before the noise removal is completed. Therefore, there has been a problem that the noise removal processing becomes complicated.

  The present invention has been made in view of such problems, and an object thereof is to provide an image correction apparatus, an image correction program, and an image correction method that can easily remove noise from an image expressed by pixel data. There is to do.

  The image correction apparatus of the present invention is an apparatus that removes noise from an image represented by pixel data, and sequentially scans each pixel, and the result of noise removal processing on the scanned pixel is scanned next time. Noise removal processing means for performing noise removal processing for each pixel so as to be reflected in the noise removal processing for the target pixel is provided.

  In this case, it is preferable that the noise removal processing means performs noise removal processing by referring to pixel data in the vicinity of each pixel.

  The image correction program of the present invention is a program for removing noise from an image expressed by pixel data, and sequentially scans each pixel, and the result of noise removal processing on the scanned pixel is scanned next time. This is reflected in the noise removal process for the target pixel, and causes the computer to execute a noise removal step for performing the noise removal process for each pixel.

  The image correction method of the present invention is a method of removing noise from an image represented by pixel data, and sequentially scanning each pixel, and the result of noise removal processing for the scanned pixel is performed for the next scanning target pixel. The noise removal processing is performed for each pixel so as to be reflected in the noise removal processing.

  In the image correction apparatus, the image correction program, and the image correction method of the present invention, each pixel is sequentially scanned in the image represented by the pixel data, and the result of the noise removal processing for the scanned pixel is the next scanning target pixel. The noise removal processing is performed for each pixel so as to be reflected in the noise removal processing.

  According to the image correction apparatus, the image correction program, or the image correction method of the present invention, the result of the noise removal processing for the scanned pixel is reflected in the noise removal processing for the next scanning target pixel while sequentially scanning each pixel. In this way, noise removal processing is performed for each pixel, so noise can be removed by scanning the entire image once, and noise can be easily removed from the image represented by the pixel data. Is possible.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[First Embodiment]
FIG. 1 shows the configuration of an image correction apparatus (image correction unit 5) according to the first embodiment of the present invention and an image for supplying a correction target image (binary imaging data Din1 described later) to the image correction apparatus. It represents the configuration of the input / output device.

  First, the configuration and operation of the image input / output device will be described.

  This image input / output device includes an input / output panel 1, a display signal generation unit 21, a display signal holding control unit 22, a display signal driver 23, a display side scanner 24, an imaging signal selection scanner 31, and an imaging signal receiver. 32 and a binarization unit 33, and displays an image based on the image data on the input / output panel 1 and uses an object (in close proximity to the input / output panel 1 using light from the display image). The imaging target object 15) to be described later is imaged.

  The input / output panel 1 includes, for example, an organic or inorganic EL (ElectroLuminescence) display or LCD (Liquid Crystal Display) in which a plurality of pixels 11 are arranged in a matrix over the entire surface, and performs line sequential operation as will be described later. While displaying an image such as a predetermined figure or character. Each pixel 11 is composed of, for example, a display imaging cell CWR including one display imaging element, and each pixel has both a display function and an imaging function as will be described later.

  Here, the details of the configuration of the input / output panel 1 will be described with reference to FIGS.

  FIG. 2 shows an example of a planar configuration of the input / output panel 1, and a total of (m × n) pixels 11 are arranged in a matrix form, with m in the horizontal line direction and n in the vertical line direction. It is assumed that This input / output panel 1 supplies (m × n) pixels 11 and display imaging cells CWR11 to CWRmn included in each pixel, and m data supplies connected according to the number of the pixels 11. It has a line DW (DW1 to DWm) and a data read line DR (DR1 to DRm), and n display gate lines G (G1 to Gn) and a switching line S (S1 to Sn).

  The data supply line DW is connected to the display signal driver 23, the data readout line DR is connected to the imaging signal receiver 32, the display gate line G is connected to the display side scanner 24, and the switching line S is connected to the imaging signal selection scanner 31. It is connected. In addition, one data supply line DW, one data read line DR, one display gate line G, and one switching line S are connected to each display imaging cell CWR. Further, for example, one vertical data display line CW11, CWR12,..., CWR1n are connected to one data supply line DW1 and data read line DR1 in common, for example, one horizontal line display imaging cell CWR11. , CWR21,..., CWRm1, one display gate line G and one switching line S are connected in common. An arrow Y in the figure indicates the scanning direction of the display gate line G and the switching line S.

  FIG. 3 schematically shows an example of the arrangement configuration of the display imaging cells CWR in the input / output panel 1 in a cross-sectional view, and corresponds to the cross section taken along the line AA in FIG.

  The input / output panel 1 includes a pair of transparent substrates 12A and 12B and a plurality of display imaging cells CWR (CW21, CW22, CW23, and the like) disposed between the transparent substrates 12A and 12B and separated from each other by a partition wall 13. CW24, CW25, ...). Each display imaging cell CWR includes, for example, an organic EL element as the display imaging element EL, and emits display light LW. In addition, about the other layer in a general organic electroluminescent display part, it is not illustrated and description is abbreviate | omitted.

  FIG. 4 shows a circuit configuration of the display imaging cell CWR in the input / output panel 1.

  The display imaging cell CWR includes a display imaging element EL, a capacitor C, a resistor R, and a data supply line DW and one end of the capacitor C according to a selection signal supplied from the display gate line G. From the switch SW1 that selectively conducts, the switch SW2 that selectively conducts between the other end of the capacitor and one end of the display imaging element EL according to the switching signal supplied from the switching line S, and the switching line S as well. A switch SW3 that selectively conducts between one end of the display imaging element EL and the data readout line DR according to the supplied switching signal is provided, and the other end of the display imaging element EL is grounded. One end of the resistor R is connected to the data read line DR, and the other end of the resistor R is connected to the ground or a negative bias point (not shown).

  Here, the operation of each component during the display operation and the imaging operation will be specifically described. First, the display operation and the imaging operation are performed using the following characteristics of the display imaging element EL. That is, for example, an organic EL element or an LED element, which is configured as the display imaging element EL in this embodiment, emits light when a forward bias voltage is applied, but receives a light and current when a reverse bias voltage is applied. It has the property of generating.

  Therefore, during the display operation, the switches SW1 and SW2 are turned on and the switch SW3 is turned off in accordance with the selection signal supplied from the display gate line G and the switching signal supplied from the switching line S. A forward bias voltage is applied to the display image sensor EL. Then, the capacitor C is charged from the data supply line DW through the path I1 so as to emit light having a luminance corresponding to the display signal, and a current flows through the display imaging element EL through the path I2 based on the charged charge. Then, the display operation is performed.

  On the other hand, during the imaging operation, according to the switching signal supplied from the switching line S, the switches SW2 and SW3 are turned off and the switch SW2 is turned on, whereby a reverse bias voltage is applied to the display imaging element EL. The Then, in the display imaging element EL, an imaging operation is performed by supplying a current corresponding to the amount of received light to the data readout line DR through a path I3.

  When neither the display operation nor the imaging operation is performed, the switches SW1 to SW3 are all off, and the data supply line DW and the data readout line DR are disconnected from the display imaging element EL, respectively. It has come to be. The resistor R connected to the data read line DR is for causing a potential difference at both ends based on the current supplied to the data read line DR through the path I3 and outputting this as an imaging signal. is there.

  Returning to the description of FIG. 1, the display signal generation unit 21 is connected to the display unit 1, for example, every screen (every frame is displayed) based on image data supplied from a CPU (Central Processing Unit) (not shown), for example. A display signal for display is generated.

  The display signal holding control unit 22 stores the display signal output from the display signal generation unit 21 for each screen (for each display of one frame), for example, in a framed memory including an SRAM (Static Random Access Memory). And hold it. The display signal holding control unit 22 also plays a role of controlling the display signal driver 23, the display side scanner 24, and the imaging signal selection scanner 31 to operate in conjunction with each other. Specifically, the display timing control signal 41 for the display-side scanner 24, the imaging timing control signal 42 for the imaging signal selection scanner 31, and the control signal and frame for the display signal driver 23. The display signals for one horizontal line based on the display signals for one screen held in the memory are each output.

  The display-side scanner 24 selects the display imaging cell CWR to be displayed according to the display timing control signal 41 output from the display signal holding control unit 22. The display signal driver 23 supplies display data to the display imaging cell CWR that is a display driving target in accordance with a display signal for one horizontal line output from the display signal holding control unit 22.

  The imaging signal selection scanner 31 selects the display imaging cell CWR to be imaged driving according to the imaging timing control signal 42 output from the display signal holding control unit 22. The imaging signal selection scanner 31 also outputs an imaging block control signal 43 to the imaging signal receiver 32 and the binarization unit 33, and also plays a role of controlling operations of portions that contribute to the imaging operation.

  The imaging signal receiver 32 acquires an imaging signal for one horizontal line output from each display imaging cell CWR in accordance with the imaging block control signal 43 output from the imaging signal selection scanner 31.

  The binarization unit 33 binarizes the image signal output from the image signal receiver 32 to a value of “0” or “1”. The binarized imaging signal (binarized imaging data Din1) is output to the image correction unit 5.

  Here, with reference to FIG. 5 and FIG. 6, an operation of capturing an image of a contacted or close object in the image display device having such a configuration will be described.

  FIG. 5 is a cross-sectional view showing an example of processing for imaging an imaging target object in the image display apparatus of FIG. 1, and the same components as those shown in FIG. The description will be omitted as appropriate.

  When an imaging target object 15 such as a finger is brought into contact with or brought close to the input / output panel 1, display light LW1 from the display imaging cell CWR (here, the display imaging cell CWR23) is reflected by the imaging target object 15. . Here, in the display imaging element EL, it is necessary to perform display operation and imaging operation in a time-sharing manner, and it is impossible to receive reflected light with the display imaging element while emitting display light with a certain display imaging element. Therefore, when the display light emitted from the display image sensor of a certain horizontal line is received by the display image sensor of another horizontal line to which the reverse bias voltage is applied, the imaging target object 15 can be imaged. For example, as shown in FIG. 5, the reflected light LR1 is incident on a display imaging cell on a horizontal line close to the display imaging cell CWR23, such as CWR24 and CWR25, but the position is far from the display imaging cell CWR23. The reflected light does not enter the display imaging cell on the horizontal line. Therefore, an imaging signal can be obtained only from the display imaging cell CWR whose position is close to a certain imaging target object 15. In this image display device, the imaging target object is emitted from the display imaging cell CWR on the horizontal line that is being driven for display. Timing driving is performed so that the light reflected at 15 is received by the display imaging cell CWR on the horizontal line adjacent to the horizontal line. In this way, an imaging signal is output from the display imaging cell CWR in the vicinity of the imaging target object 15, but no imaging signal is output from other areas, so that the imaging target object 15 is placed on the input / output panel 1. Which region is located is detected, and an imaging operation can be performed.

  Further, as shown in FIG. 6, by performing such display driving and imaging driving sequentially for each horizontal line (line sequential driving), the imaging target object 15 is displayed while displaying an image on the entire input / output panel 1. Can be imaged. In FIG. 6, reference numerals P2, P3, P8, and P9 represent the positions of lines being scanned, reference numerals 61, 61A, and 61B represent display areas, and reference numeral 63 represents an imaging area.

  Next, the configuration of the image correction apparatus (image correction unit 5) will be described with reference to FIG. 1 and FIGS.

  This image correction device (image correction unit 5) includes a frame memory 51, a scanning unit 52, a calculation unit 53, and a setting unit 54, and an imaging signal (binarization) supplied from the image input / output device. Image correction of the binarized imaging data Din1 is performed by removing noise from the imaging data Din1). The image correction method according to the present embodiment is embodied by the image correction apparatus according to the present embodiment, and will be described below.

  The frame memory 51 is a memory that receives the binarized imaging data Din1 through the scanning unit 52 and holds data for one screen (one frame). The binarized imaging data Din1 for one frame held in this way constitutes an image as shown in FIG. 7, for example, and is expressed as a set of binarized imaging data Din1 as pixel data. It has become. Note that reference numerals 11W and 11B in the drawing represent white display pixels or black display pixels, respectively, and indicate pixels whose value (pixel data) of the binarized imaging data Din1 is “1” or “0”, respectively. Yes.

  The scanning unit 52 supplies the binarized imaging data Din1 supplied from the binarizing unit 33 of the image input / output device to the frame memory 51 and, for example, as shown by an arrow X in FIG. The target pixel 71 is sequentially scanned on an image of one frame expressed by the following. Further, the scanning unit 52 refers to pixel data (values of the binarized imaging data Din1) of pixels in the vicinity of the target pixel 71 (in this case, eight neighboring pixels 72 surrounding the target pixel 71), and The pixel data of the neighboring pixels 72 are output to the calculation unit 53, respectively.

  The calculation unit 53 calculates the sum of the pixel data of the neighboring pixels 72 supplied from the scanning unit 52 and outputs the obtained sum (pixel total value Sout) of the pixel data to the setting unit 54.

  The setting unit 54 refers to a pixel value setting table 81 as illustrated in FIG. 9 based on the pixel total value Sout supplied from the calculation unit 53, for example, so that the target pixel 71 held in the frame memory 51 is obtained. Is forcibly set, and noise removal processing of the binarized imaging data Din1 is selectively performed. Specifically, when the total pixel value Sout is equal to or less than the black threshold value (in this case, black threshold value = 1), the pixel value of the target pixel is set to the binarized data “0”. When the pixel total value Sout is equal to or greater than the white threshold value (in this case, the white threshold value = 5), the pixel value of the target pixel is set to the binarized data “1”. . Further, when the total pixel value Sout is between the black threshold value and the white threshold value (in this case, Sout = 2 to 4), the pixel value of the target pixel is not changed. The black threshold value and the white threshold value are not limited to the values shown in FIG. 9, and any number can be set. The image data after noise removal processing (noise-removed imaging data Dout) obtained in this way is output from the frame memory 51 to the outside of the image correction unit 5 and used for other processing. ing.

  Here, the calculation unit 53 and the setting unit 54 correspond to a specific example of “noise removal means” in the present invention.

  Next, noise removal processing by the image correction apparatus (image correction unit 5) according to the present embodiment will be described with reference to FIGS. Here, FIG. 10 is a flowchart showing the noise removal processing according to the present embodiment, and FIGS. 11 to 13 show the modes of the noise removal processing divided into three cases, respectively. .

  First, the scanning unit 52 advances the target pixel 71 by sequentially scanning each pixel on the frame memory 51 as indicated by an arrow X in FIG. 8 (step S101 in FIG. 10). Next, the calculation unit 53 obtains the sum (pixel total value Sout) of the neighboring pixels 72 based on the pixel data of the neighboring pixels 72 supplied from the scanning unit 52 (step S102).

  Next, the setting unit 54 refers to the pixel value setting table 81 as shown in FIG. 9, for example, based on the pixel total value Sout supplied from the calculation unit 53, so that attention is paid on the frame memory 51. The pixel value of the pixel 71 is forcibly set, and the noise removal processing of the binarized imaging data Din1 is selectively performed. Specifically, the setting unit 54 first determines whether or not the total pixel value Sout is less than or equal to the black threshold value (in this case, black threshold value = 1), that is, whether Sout ≦ 1 (step S103). ).

  When Sout ≦ 1 (step S103: Y), for example, as shown in FIGS. 11A to 11D, the pixel value of the target pixel 71 is set to the binarized data “0”, that is, the target pixel 71 Is set as a black display pixel (step S104). Specifically, in this case, as shown in FIG. 11B, out of the eight neighboring pixels 72, seven black display pixels (pixel data = 0) and one white display pixel (pixel data = 1) are included. Therefore, the pixel total value Sout = 1 of these neighboring pixels 72 is set, and the setting of the target pixel 71 is changed from the white display pixel to the black display pixel as shown in FIG. 11C. . In this way, it is determined that the target pixel 71 is noise, and noise removal processing is performed. Thereafter, the process proceeds to step S107 described later.

  On the other hand, when Sout> 1 (step S103: N), the setting unit 54 next determines whether or not the pixel total value Sout is equal to or larger than the white threshold value (in this case, white threshold value = 5), that is, Sout ≧ Whether it is 5 or not is determined (step S105).

  When Sout ≧ 5 (step S105: Y), for example, as shown in FIGS. 12A to 12D, the pixel value of the target pixel 71 is set to the binarized data “1”, that is, the target pixel 71 Are set as white display pixels (step S106). Specifically, in this case, as shown in FIG. 12B, among the eight neighboring pixels 72, three black display pixels (pixel data = 0) and five white display pixels (pixel data = 1) are present. Therefore, the total pixel value Sout of these neighboring pixels 72 becomes 5, and the target pixel 71 is changed from the black display pixel to the white display pixel as shown in FIG. . In this way, it is determined that the target pixel 71 is noise, and noise removal processing is performed. Thereafter, the process proceeds to step S107 described later.

  On the other hand, when Sout <5 (step S105: N), the pixel total value Sout is between the black threshold value and the white threshold value (in this case, Sout = 2 to 4). As shown in (A) to (D), the process proceeds to step S107 without changing the pixel value of the target pixel 71. Specifically, in this case, as shown in FIG. 13B, among the eight neighboring pixels 72, five black display pixels (pixel data = 0) and three white display pixels (pixel data = 1) are present. Therefore, the total pixel value Sout of these neighboring pixels 72 becomes 3, and as shown in FIG. 13C, the target pixel 71 remains the white display pixel and is not changed. In this way, it is determined that the target pixel 71 is not noise, and noise removal processing is avoided.

  Finally, the scanning unit 52 determines whether all the pixels have been completed, that is, whether all the pixels on the frame memory 51 have been scanned (step S107). When it is determined that all the pixels have not been completed yet (step S107: N), the process returns to step S101. On the other hand, when it is determined that all the pixels have been completed (step S107: Y), noise removal is performed. The process ends. In this way, all the noise removal processing for one screen on the frame memory 51 is performed.

  Next, with reference to FIGS. 7 and 14 to 17, an example in which the above-described noise removal processing is performed on the imaging data illustrated in FIG. 7 will be described.

  First, as shown in FIGS. 14A to 14C, noise removal processing is performed while sequentially scanning the target pixel 71, thereby generating image data by an image input / output device having a display function and an imaging function. Line noise (in this case, noise due to white display pixels) that tends to be removed is removed.

  Next, for example, as shown in FIGS. 15A and 15B, isolated pixel noise due to white display pixels is removed, while as shown in FIGS. 16A and 16B, for example. Isolated pixel noise due to white display pixels is removed.

  In this way, when the noise removal processing described above is performed on the imaging data shown in FIG. 7, the result is as shown in FIG. That is, as indicated by reference numeral N1, line-like noise that tends to occur in image data by an image input / output device having a display function and an imaging function is removed, and as indicated by reference numerals N2 and N3, respectively. It can be seen that isolated pixel noise due to white display pixels or black display pixels is also removed.

  As described above, in the noise removal processing according to the present embodiment, as shown in FIGS. 14 to 16, in the captured image represented by the pixel data, each pixel is sequentially scanned and the scanned pixel is scanned. The noise removal process is performed for each pixel so that the result of the noise removal process is reflected in the noise removal process for the next pixel to be scanned.

  As described above, in the present embodiment, the scanning unit 52 sequentially scans each pixel of the image based on the binarized imaging data Din1 for one screen held in the frame memory 51, and the calculation unit 53 and the setting unit. 54 reflects the result of the noise removal process for the scanned pixel in the noise removal process for the next pixel to be scanned, and the noise removal process is performed for each pixel. Noise can be removed only by scanning, and noise can be easily removed from the image represented by the binarized imaging data Din1 for one screen.

  In addition, by performing such noise removal processing, it is possible to remove line-like noise that tends to occur in imaged data from an image input / output device having a display function and an imaging function, and to display white. Isolated pixel noise due to pixels or black display pixels can also be removed.

  Further, since the pixel data of the pixel in the vicinity of the target pixel 71 (neighboring pixel 72) is referred to, the noise removal processing can be performed in consideration of the state of the neighboring pixel 72, and more accurate noise can be obtained. Removal can be performed.

  Further, since it is performed based on the sum of pixel data of the neighboring pixels 72 (pixel total value Sout), it can be performed more easily than in the case of performing a general pixel pattern matching process.

  Furthermore, since the pixel value of the pixel of interest 71 is set by providing a white threshold value or a black threshold value, the sensitivity of noise removal can be adjusted by adjusting these threshold values. It becomes.

[Second Embodiment]
Next, a second embodiment of the present invention will be described.

  In the first embodiment, the noise removal processing in the case where the imaging data supplied to the image correction unit 5 is binarized data (binary imaging data Din1) has been described. In the embodiment, a description will be given of noise removal processing in a case where imaging data supplied to the image correction unit 5 is gradation data (multi-valued imaging data Din2) expressed in a multivalued manner. In order to simplify the description, the same parts as those in the first embodiment will be described below with the same reference numerals.

  FIG. 18 shows the configuration of the image correction apparatus (image correction unit 5) according to the present embodiment and the configuration of an image input / output apparatus that supplies multivalued imaging data Din2 to the image correction apparatus. The difference from the case of the first embodiment shown in FIG. 1 is that the binarization unit 33 is omitted from the image input / output device, and the determination unit 55 and the binarization unit 56 are provided in the image correction unit 5. This is the point.

  The determination unit 55 determines in which range the pixel data of the target pixel 71 represented by multi-values supplied from the scanning unit 52 is in the gradation level. Specifically, when the pixel data of the pixel of interest 71 is expressed with a luminance gradation level as shown in FIG. 19, for example, the gradation level of the pixel data of the pixel of interest is from the minimum luminance level Ymin. Within first region Y1 up to first threshold Yth1, within second region Y2 from first threshold Yth1 to second threshold Yth2, and highest from second threshold Yth2 It is determined which region in the third region Y3 up to the luminance level Ymax is present. The minimum luminance level Ymin is 0 gradation level (black level), and the maximum luminance level Ymax is, for example, 255 gradation level (white level). The first threshold value Yth1 is, for example, about 10 gradation levels, and the second threshold value Yth2 is, for example, about 100 gradation levels. The threshold value Yth in the figure represents a binarization threshold value in a binarization unit 56 described later.

  The determination unit 55 sets the pixel value of the target pixel 71 by referring to the pixel value setting table 82 as shown in FIG. 20, for example, based on the determination result of the gradation level. It has become. Specifically, when the gradation level is in the Y1 region, the pixel data of the target pixel 71 is output to the binarization unit 56 as it is, and the binarization unit 56 binarizes the target data. The pixel value of the pixel 71 is set to binarized data “0”. When the gradation level is within the Y3 region, the pixel data of the target pixel 71 is output to the binarization unit 56 as it is, and the binarization unit 56 binarizes the pixel data of the target pixel 71. The pixel value is set to binary data “1”. On the other hand, when the gradation level is within the Y2 region, the pixel data of the pixel of interest 71 and its neighboring pixels 72 are output to the binarization unit 56, respectively, and this neighboring pixel 72 is the same as in the first embodiment. The pixel value of the target pixel 71 is set by the total pixel value Sout.

  The binarization unit 56 binarizes the pixel data of the target pixel 71 or the pixel data of the neighboring pixel 72 supplied from the determination unit 55 and outputs the binarized pixel data of the target pixel to the frame memory 51. The binarized pixel data of neighboring pixels is output to the calculation unit 53.

  Next, with reference to FIG. 21, the noise removal processing by the image correction apparatus (image correction unit 5) of the present embodiment will be described. FIG. 21 is a flowchart showing the noise removal process according to the present embodiment.

  First, similarly to step S101 described in the first embodiment, the scanning unit 52 sequentially scans each pixel on the frame memory 51 to advance the target pixel 71 (step S201). Next, the determination unit 55 determines the luminance gradation level of the target pixel 71 supplied from the scanning unit 52 (step S202).

  If it is determined in step S202 that the region is the “Y1 region”, the determination unit 55 is away from the binarization threshold Yth in the case of the Y1 region, and therefore when binarizing the pixel data of the pixel of interest 71. It is determined that no noise is generated (step S203), and the pixel data of the target pixel 71 is output to the binarization unit 56. Then, the binarization unit 56 binarizes, so that the pixel value of the target pixel 71 is set to the binarized data “0” and is written on the frame memory 51 (step S204). Thereafter, the process proceeds to step S212 described later.

  If it is determined in step S202 that the region is the “Y3 region”, the determination unit 55 is separated from the binarization threshold Yth if the region is the Y3 region. It is determined that no noise is generated during conversion (step S205), and the pixel data of the target pixel 71 is output to the binarization unit 56. Then, the binarization unit 56 binarizes, so that the pixel value of the target pixel 71 is set to the binarized data “1” and is written on the frame memory 51 (step S206). Thereafter, the process proceeds to step S212 described later.

  On the other hand, if it is determined in step S202 that the region is the “Y2 region”, the determination unit 55 includes the binarized threshold value Yth in the case of the Y2 region, so that the pixel data of the pixel of interest 71 is 2 It is determined that noise may be generated in the binarization (step S207), and the pixel data of the target pixel 71 and the pixel data of the neighboring pixel 72 are output to the binarization unit 56. Then, the binarizing unit 56 binarizes the pixel data of the target pixel 71 and its neighboring pixels 72 (step S208).

  After step S208, as in steps S102 and S103 described in the first embodiment, the calculation unit 53 obtains the pixel total value Sout of the neighboring pixels 72 (step S209), and the setting unit 54 first sets, for example, Sout It is determined whether or not ≦ 1 (step S210). When it is determined that Sout ≦ 1 is satisfied (step S210: Y), the pixel value of the target pixel 71 is set to “0” (step S204), and the process proceeds to step S212. On the other hand, when it is determined that Sout> 1 (step S210: N), the setting unit 54 next determines whether, for example, Sout ≧ 5, as in step S105 described in the first embodiment. (Step S211). If it is determined that Sout ≧ 5 (step S211: Y), the pixel value of the target pixel 71 is set to “1” (step S206), and the process proceeds to step S212. On the other hand, if it is determined that Sout <5 (step S211: Y), the process proceeds to step S212.

  Finally, similarly to step S107 described in the first embodiment, the scanning unit 52 determines whether all pixels have been completed (step S212). When it is determined that all the pixels have not been completed yet (step S212: N), the process returns to step S201. On the other hand, when it is determined that all the pixels have been completed (step S212: Y), noise removal is performed. The process ends.

  As described above, in the present embodiment, the determination unit 55 determines the gradation level of the multivalued imaging data Din2 supplied from the image input / output device, and the determined gradation level is within a predetermined range ( The binarization unit 56 binarizes the multi-valued imaging data Din2 only when it is in the second region Y2 from the first threshold value Yth1 to the second threshold value Yth2). Since the selective noise removal process described in the embodiment is performed, it is possible to reduce the burden of the noise removal process when the imaging data is multilevel data.

  Further, when it is determined that the gradation level of the multilevel imaging data Din2 is within the Y1 region, the binarization unit 56 binarizes the pixel value of the target pixel 71 to be forcibly set to 2. On the other hand, when the gradation level is within the Y3 region while the binarized data “0” is set, the pixel value of the target pixel 71 is forcibly set to the binarized data “1”. If there is a low possibility of noise during binarization, binarization processing can be performed without worrying about noise generation.

  Although the present invention has been described with reference to the first and second embodiments, the present invention is not limited to these embodiments, and various modifications can be made.

  For example, in the above embodiment, the case where the pixel of interest 71 scans the line at the end of the image is not described, but the pixel of interest is the image of the image like the pixels of interest 71A and 71B shown in FIG. You may make it scan also on an edge line. Further, in this configuration, the calculation of the pixel total value Sout of the neighboring pixels is performed only for the neighboring pixels 72A1 and 72B1 in the image and not for the neighboring pixels 72A2 and 72B2 outside the image. The white threshold value and the black threshold value may be adjusted according to the number of neighboring pixels 72A1 and 72B1. Alternatively, the neighboring pixels 72A2 and 72B2 outside the image may be calculated on the assumption that the pixel data is virtually “0”.

  In the above embodiment, the case where the scanning unit 52 sequentially scans each pixel from one end of the image has been described. However, as illustrated in FIG. 23, for example, both ends (start position and end position) of the pixel array of the image ), As indicated by arrows X1 and X2, they may be scanned in parallel in opposite directions. When configured in this way, in addition to the effects in the above-described embodiment, it is possible to shorten the noise processing time.

  In the above-described embodiment, a case has been described in which it is determined whether the target pixel 71 is noise based on the pixel total value Sout of the neighboring pixels 72 and noise removal processing is performed. It may be determined whether noise is present, and noise removal processing may be performed. Even in such a configuration, if the result of the noise removal process is reflected in the noise removal process for the next pixel to be searched, it is possible to obtain the same effect as the above embodiment. is there.

  In the above-described embodiment, the pixel in the vicinity of the target pixel 71 has been described as being configured by the eight neighboring pixels 72 surrounding the target pixel. However, the configuration of the neighboring pixels is not limited to this, and any arbitrary pixel may be used. It can be constructed from a range.

  Further, in the above-described embodiment, a pixel whose value (pixel data) of the binarized imaging data Din1 is “0” becomes the black display pixel 11B, and a pixel whose pixel data is “1” becomes the white display pixel 11W. The case of the input / output panel 1 has been described. Conversely, in the present invention, a pixel whose pixel data is “0” is a white display pixel 11W, and a pixel whose pixel data is “1” is a black display pixel 11B. The present invention can also be applied to the case of an input / output panel.

  In the above embodiment, the case where the input / output panel 1 is configured by the display imaging element EL having both the display function and the imaging function has been described. However, a display element having a display function (for example, a liquid crystal element or LED (Light An input / output panel may be configured by separately providing an element having an imaging function (for example, a photodiode or a CCD (Charge Coupled Device)).

  Moreover, although the case where a series of noise removal processes are performed by hardware was demonstrated in the said embodiment, these processes can also be performed by software. In the case of such a configuration, by installing a program constituting software for executing a series of noise removal processes in a computer incorporated in dedicated hardware, the series of noise removal processes is performed on the computer. Can be executed.

  Furthermore, in the above-described embodiment, the case of performing noise removal processing of imaging data supplied from the image input / output device has been described, but the present invention is not limited to imaging data from such an image input / output device, The present invention can be applied to any image expressed by pixel data. For example, the noise removal processing of the present invention can be applied to an image captured from a scanner or an image received by a facsimile.

It is a block diagram showing the structure of the image correction apparatus and image input / output device which concern on the 1st Embodiment of this invention. It is a top view showing the structure of the input-output panel shown in FIG. It is sectional drawing which represents typically an example of the arrangement configuration of the display imaging cell in an input-output panel. It is a circuit diagram showing the structure of the display imaging cell shown in FIG. FIG. 2 is a schematic cross-sectional view illustrating an example of a process for imaging an imaging target object in the image input / output device illustrated in FIG. 1. It is a schematic diagram showing an example of a line sequential display operation and a line sequential imaging operation in the input / output panel. It is a schematic diagram showing the structural example of the image expressed with imaging data. It is a schematic diagram for demonstrating the scanning direction of an attention pixel, and the position of a neighboring pixel. It is a schematic diagram showing the pixel value setting table which concerns on 1st Embodiment. It is a flowchart showing the noise removal process which concerns on 1st Embodiment. It is a schematic diagram for demonstrating the noise removal process shown in FIG. It is a schematic diagram for demonstrating the noise removal process shown in FIG. It is a schematic diagram for demonstrating the noise removal process shown in FIG. It is a schematic diagram for demonstrating the noise removal process with respect to the image shown in FIG. It is a schematic diagram for demonstrating the noise removal process following FIG. It is a schematic diagram for demonstrating the noise removal process following FIG. It is a schematic diagram for demonstrating the image after a noise removal process. It is a block diagram showing the structure of the image correction apparatus and image input / output device which concern on 2nd Embodiment. It is a schematic diagram for demonstrating the relationship between the gradation level of the brightness | luminance of image data, and a threshold value. It is a schematic diagram showing the pixel value setting table which concerns on 2nd Embodiment. It is a flowchart showing the noise removal process which concerns on 2nd Embodiment. It is a schematic diagram for demonstrating the noise removal process which concerns on the modification of this invention. It is a schematic diagram for demonstrating the noise removal process which concerns on the other modification of this invention.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Input-output panel, 11 ... Pixel, 11W ... White display pixel, 11B ... Black display pixel, 12A, 12B ... Transparent substrate, 13 ... Bulkhead, 15 ... Object to be imaged, 21 ... Display signal generation part, 22 ... Display signal Holding control unit, 23 ... display signal driver, 24 ... display side scanner, 31 ... imaging signal selection scanner, 32 ... imaging signal receiver, 33, 56 ... binarization unit, 41 ... display timing control signal, 42 ... imaging timing control Signal, 43 ... Imaging block control signal, 5 ... Image correction unit, 51 ... Frame memory, 52 ... Scanning unit, 53 ... Calculation unit, 54 ... Setting unit, 55 ... Determination unit, 61, 61A, 61B ... Display area, 63 Image pickup area, 71, 71A, 71B, 711, 712 ... Pixel of interest, 72, 72A1, 72A2, 72B1, 72B2, 721, 722 ... Neighboring pixels, 81, 82 ... Pixel value setting Table, CWR ... display imaging cell, DW ... data supply line, DR ... data readout line, G ... display gate line, S ... switching line, LW, LW1 ... display light, LR1 ... reflected light, EL ... display imaging device, C ... capacitor, R ... resistor, SW1, SW2, SW3 ... switch, I1 ... display signal current path, I2 ... imaging signal current path, Y ... scan direction, P2, P3, P8, P9 ... horizontal line position during scanning , X, X1, X2 ... scanning direction, Sout ... total pixel value, N1, N2, N3 ... noise, Yht1 ... first threshold, Yth2 ... second threshold.

Claims (9)

An image correction apparatus that removes noise from an image represented by pixel data,
Scanning means for sequentially scanning each pixel;
And a noise removal processing means for performing noise removal processing for each pixel so that the result of noise removal processing for the scanned pixel is reflected in the noise removal processing for the next pixel to be scanned. An image correction device. The image correction apparatus according to claim 1, wherein the noise removal processing unit performs noise removal processing by referring to neighboring pixel data for each pixel. The pixel data is a binary representation of luminance,
The noise removal processing unit obtains a sum of pixel data of pixels in the vicinity of the target pixel, and selectively performs noise removal processing based on the obtained sum of pixel data. Image correction device. The noise removal processing unit sets the value of the target pixel to “0” when the sum of the pixel data is equal to or less than a predetermined threshold value, while the sum of the pixel data is less than the predetermined threshold value. 4. The image correction apparatus according to claim 3, wherein the noise correction process is selectively performed by setting the value of the target pixel to “1” when the threshold value is larger than another large threshold value. 5. The input pixel data is gradation data representing multi-valued luminance,
The noise removal processing means performs the noise removal processing after binarizing the pixel and its neighboring pixel data only when the input pixel data is within a predetermined gradation range. The image correction apparatus according to claim 2. The predetermined gradation range is a gradation range from a first threshold value to a second threshold value greater than this value;
The noise removal processing unit sets the pixel to binarized data “0” when the input pixel data is equal to or less than the first threshold value, while the input pixel data is the second pixel data. The image correction apparatus according to claim 5, wherein the pixel is set to binarized data “1” when the threshold value is equal to or greater than the threshold value. The image correction apparatus according to claim 1, wherein the scanning unit scans pixels in parallel in opposite directions from the start point position and the end point position of the pixel array of the input image. An image correction program for removing noise from an image represented by pixel data,
A scanning step of sequentially scanning each pixel;
The result of the noise removal processing for the scanned pixel is reflected in the noise removal processing for the next pixel to be scanned, and the computer performs a noise removal step for performing noise removal processing for each pixel. An image correction program. An image correction method for removing noise from an image represented by pixel data,
Scan each pixel sequentially,
An image correction method comprising: performing noise removal processing for each pixel so that the result of noise removal processing for a scanned pixel is reflected in noise removal processing for the next pixel to be scanned.

Images