JP4962159B2 - Measuring apparatus and method, program, and recording medium - Google Patents

Description

  The present invention relates to a measuring apparatus and method, a program, and a recording medium, and more particularly, to a measuring apparatus and method, a program, and a recording medium that enable more appropriate noise correction.

  There are many methods for calculating the noise level from the image data value. A method for defining a temporal difference below a certain fixed value as noise, a method for performing the same discrimination after applying motion correction, and image data as frequency components. There is a method of converting and defining noise below a certain fixed power.

  In addition, as a method of discriminating noise without using a fixed value, the input video signal is divided into a plurality of small blocks on the screen, and for each pixel of each divided small block, time is taken within the video signal and each of the small blocks. The difference with the signal averaged in the axial direction is obtained, and the distribution of these differences is compared with the noise distribution of the statistical distribution rule prepared for detecting the S / N value in advance, and the significance is obtained. It has also been proposed to obtain an S / N value occurrence frequency based on the difference between the small blocks and detect an effective S / N value from the distribution of the occurrence frequency (see, for example, Patent Document 1).

  In addition, there are a method in which the smallest set of fluctuations are assumed to be noise, and a method in which similar noise discrimination is performed after image motion correction.

JP-A-8-201464

  However, in the conventional technique, the amount of noise is calculated from each pixel value of the image data, and the amount of noise obtained in this way may be different from the level of noise actually recognized by a person. For example, even if the amount of noise is the same as a numerical value, people feel that there is a lot of noise in the case of an image with small motion, an image with few edges, and in the case of an image with large motion, an image with many edges, I feel that there are few.

  In other words, images with small movements or images with few edges (for example, images where the same object is large in the same place in the same place and taken for a long time) are displayed with the same image for a certain amount of time, so there is a slight change. It becomes easy to feel.

  Also, in the image, for example, the noise of a part that a person pays attention to, such as a human face part, is worrisome even if it is minute.

  The present invention has been made in view of such circumstances, and makes it possible to perform more appropriate noise correction.

One aspect of the present invention is a measuring device that measures a noise level of a video signal, and in image data for one frame based on an input video signal, a plurality of pixels configured by a predetermined number of pixels in the image data. Control information generating means for generating control information for each of the regions, and image data for one frame earlier in time for each of the plurality of regions where the control information is generated based on the input video signal Difference data acquisition means for acquiring difference data between each pixel value and each pixel value constituting image data for one frame later in time, and each pixel value of the plurality of regions of the frequency of the difference value, by setting the frequency of the difference of the values of the pixels multiplied by the coefficient determined in response to the control information of the region, by the difference data acquisition means Comprising a histogram data generating means for generating a resulting Histogram data of the difference data, and a noise amount calculating means for calculating a noise amount of the input video signal based on said histogram data generated by said histogram data generating means The control information generating means calculates the number of image edges in the region, the average value of the luminance of the pixels in the region, or a calculated value representing the amount of movement of the pixels in the region, and the smaller the calculated value, It is a measuring device that generates the control information so that the value of the coefficient becomes large .

One aspect of the present invention is a measurement method of a measurement apparatus that measures a noise level of a video signal, and is configured by a predetermined number of pixels in the image data in one frame of image data based on an input video signal. Control information is generated for each of the plurality of regions, and each of the plurality of regions where the control information is generated based on the input video signal constitutes image data for one frame earlier in time. The difference value between the pixel value and the value of each pixel constituting the image data for one frame later in time is acquired, and the frequency of the difference value between the pixel values of the plurality of regions is obtained . set the frequency difference of the values of the pixels multiplied by the coefficient determined in response to the control information of the region, the histogram data of the difference data to which the acquired, the product Generated based on the control information comprises the step of calculating a noise amount of the input video signal on the basis of the histogram data said generated number of edges of the image in the area, the average luminance of pixels in the region In the measurement method, the control information is generated such that a value or a calculated value representing a motion amount of a pixel in the region is calculated, and the coefficient value increases as the calculated value decreases .

One aspect of the present invention is a program for causing a computer to measure a noise level of a video signal, and the computer is configured with a predetermined number of pixels in the image data in one frame of image data based on the input video signal. Control information generating means for generating control information for each of a plurality of regions, and an image corresponding to one frame earlier in time for each of the plurality of regions where the control information is generated based on the input video signal Difference data acquisition means for respectively acquiring difference data between the values of the respective pixels constituting the data and the values of the respective pixels constituting the image data for one frame later in time, and each of the plurality of regions Set the frequency of the difference value of the pixel value by multiplying the frequency of the difference value of the pixel value by a coefficient determined corresponding to the control information of the area Te, calculates the amount of noise of the input video signal the difference histogram data generating means for generating histogram data of the obtained the difference data is the data acquisition means, based on the generated the histogram data was by the histogram data generating means The control information generating means calculates a number of image edges in the region, an average value of luminance of pixels in the region, or a calculated value representing a motion amount of pixels in the region. A program that functions as a measurement device that generates the control information so that the value of the coefficient increases as the calculated value decreases .

In one aspect of the present invention, in one frame of image data based on an input video signal, in one frame of image data based on the input video signal, a plurality of pixels configured by a predetermined number of pixels in the image data are provided. Control information is generated for each of the regions, and the values of the respective pixels constituting the image data for the previous frame in terms of time for each of the plurality of regions where the control information is generated based on the input video signal Difference data of the values of the respective pixels constituting the image data for one frame later in time is acquired, and the frequency of the difference value of the values of the respective pixels of the plurality of regions set the frequency difference of the values of the pixels multiplied by the coefficient determined in response to the control information, the histogram data of the difference data to which the acquired are pre It is generated based on the generated control information, the noise amount of the input video signal on the basis of the histogram data the generated is calculated. Also, the number of image edges in the region, the average value of the luminance of the pixels in the region, or a calculated value representing the amount of movement of the pixels in the region is calculated, and the coefficient value increases as the calculated value decreases. As described above, the control information is generated.

  According to the present invention, more appropriate noise correction can be performed.

  Embodiments of the present invention will be described below. Correspondences between constituent elements of the present invention and the embodiments described in the specification or the drawings are exemplified as follows. This description is intended to confirm that the embodiments supporting the present invention are described in the specification or the drawings. Therefore, even if there is an embodiment which is described in the specification or the drawings but is not described here as an embodiment corresponding to the constituent elements of the present invention, that is not the case. It does not mean that the form does not correspond to the constituent requirements. Conversely, even if an embodiment is described here as corresponding to a configuration requirement, that means that the embodiment does not correspond to a configuration requirement other than the configuration requirement. It's not something to do.

A measuring apparatus according to one aspect of the present invention is a measuring apparatus (for example, the noise level measuring apparatus 10 in FIG. 1) that measures a noise level of a video signal, and in the image data for one frame based on an input video signal, control information generating means for generating for each control information of a plurality of regions composed of a predetermined number of pixels in the image data (e.g., the effective area control unit 21 of FIG. 1) and, based on the input video signal, the For each of the plurality of regions in which the control information is generated, the values of the respective pixels constituting the image data for one frame earlier in time and the respective image data constituting the image data for one frame later in time the difference data of pixel values, the difference data acquisition means for each acquisition (e.g., frame difference obtaining unit 31 of FIG. 1), the difference between the value of each pixel of said plurality of areas Of the frequency, by setting the frequency of the difference of the values of the pixels multiplied by the coefficient determined in response to the control information of the region, the histogram data of the difference data obtained by said difference data acquisition means, Histogram data generation means (for example, the histogram generation unit 32 in FIG. 1) generated based on the control information generated by the control information generation means, and the input based on the histogram data generated by the histogram data generation means A noise amount calculation unit (for example, a noise amount calculation unit 33 in FIG. 1) for calculating a noise amount of the video signal, and the control information generation unit calculates the number of edges of the image in the region and the luminance of the pixel in the region. An average value or a calculated value representing the amount of movement of pixels in the region is calculated, and the smaller the calculated value, the more the coefficient As it increases, and generates the control information.

A measurement method according to one aspect of the present invention is a measurement method of a measurement device (for example, the noise level measurement device 10 in FIG. 1) that measures the noise level of a video signal, and image data for one frame based on an input video signal. Control information is generated for each of a plurality of regions composed of a predetermined number of pixels in the image data (for example, the process of step S11 in FIG. 3), and the control information based on the input video signal is For each of the plurality of generated areas, the value of each pixel constituting the image data for one frame earlier in time and the value of each pixel constituting the image data for one frame later in time the differential data, respectively obtained (for example, step S12 in FIG. 3), the frequency of the difference of the values of each pixel of said plurality of regions, the control information of the area Multiplied by the coefficient determined in response to set the frequency of the difference of the values of the pixel, the histogram data of the difference data to which the acquired, generated based on the generated control information (e.g., Fig. 3), and calculating the noise amount of the input video signal based on the generated histogram data (for example, the process of step S15 in FIG. 3) , The control information is calculated such that the number of edges of the pixel, the average value of the luminance of the pixels in the region, or a calculated value representing the amount of motion of the pixel in the region is calculated, and the value of the coefficient increases as the calculated value decreases. Is generated .

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 1 is a block diagram showing a configuration example of a noise level measuring apparatus according to an embodiment of the present invention.

  For example, the noise level measuring apparatus 10 measures the noise level of the video signal based on the input video signal and outputs the measurement result. The measurement result output from the noise level measuring apparatus 10 is as follows. For example, it is used for control of a noise reducer that removes noise in an image (video).

  As shown in the figure, the noise level measuring apparatus 10 includes an effective area control unit 21 and a noise measuring unit 22. The input video signal is supplied to the effective area control unit 21 to generate a control signal relating to an area from which noise is to be removed, as will be described later, and based on the control signal output from the effective area control unit 21, the noise measurement unit 22 Noise measurement is controlled.

  The noise measurement unit 22 includes a frame difference acquisition unit 31, a histogram generation unit 32, and a noise amount calculation unit 33.

  Based on the input video signal, the frame difference acquisition unit 31 determines the luminance value of each pixel constituting the temporally previous frame image and the luminance value of each pixel constituting the temporally subsequent frame image. The difference absolute value is calculated. That is, the frame difference acquisition unit 31 calculates the absolute difference value of the luminance values of the corresponding pixels between frames (temporally preceding frame and temporally subsequent frame).

  The histogram generation unit 32 generates a histogram that is statistical data for calculating the amount of noise based on the data output from the frame difference acquisition unit 31. In this histogram, for example, the horizontal axis represents the difference absolute value for each pixel between frames, and the vertical axis represents the frequency (the number of pixels having the difference absolute value).

  If the change in luminance value between frames is large, the number of pixels with a large absolute difference between frames will increase, so the peak of the histogram is formed on the right side (the value on the horizontal axis is far from zero) When the change in luminance value between frames is small, the number of pixels with a small absolute value between frames increases, so the peak of the histogram is formed on the left side (the value on the horizontal axis is close to zero). It will be.

  In addition, the histogram generation unit 32 generates a histogram based on the control signal supplied from the effective area control unit 21. For example, the histogram generation unit 32 sets the frequency corresponding to the difference absolute value for each pixel between predetermined frames higher than the actual frequency based on the weighting factor included in the control signal supplied from the effective region control unit 21. Or set it low.

  The absolute difference between frames may be calculated not in units of pixels but in units of blocks including a predetermined number of pixels, and a histogram may be generated. In this case, for example, the variance value of the block is calculated based on the absolute difference value between the frames of pixels constituting one block, and the horizontal axis is the variance value of the block, and the number of blocks having the variance value is calculated. A histogram may be generated with the represented frequency as the vertical axis.

  The noise amount calculation unit 33 calculates the noise amount of the video signal based on the histogram data supplied from the histogram generation unit 32 (for example, information indicating the frequency corresponding to each difference absolute value for each pixel). The noise amount calculation unit 33 is a noise corresponding to a change between frames of the video signal so that it can be identified whether the change is highly likely to be a noise according to a change between frames of the video signal. An amount is calculated.

  That is, in the histogram generated by the histogram generation unit 32, the noise amount calculation unit 33 calculates a relatively large amount of noise as the peak position is on the right side. In the histogram generated by the above, the noise amount of a relatively small value is calculated as the peak position is on the left side.

  The noise amount calculated by the noise amount calculation unit 33 is set to a noise level by, for example, normalization according to a predetermined standard, and is output as a measurement result of the noise level measurement device 10.

  By the way, when the amount of noise is calculated from each pixel value such as a video signal and image data, the calculated amount of noise may not correspond to noise that is actually recognized by a person. For example, even if the numerical value of the amount of noise calculated from each pixel value such as a video signal and image data is the same, in the case of an image with small motion or an image with few edges, a person feels that there is a lot of noise, In the case of large images or images with many edges, people feel that there is less noise.

  That is, an image with small motion or an image with few edges is likely to feel minute changes because the same image continues to be displayed for a certain period of time. If the amount of noise corresponding to the characteristics of human visibility is not calculated, for example, an image obtained by performing noise removal processing with a noise reducer or the like may become unnatural. .

  Therefore, the noise level measuring apparatus 10 of the present invention is provided with an effective area control unit 21. The effective area control unit 21 specifies an effective area from which noise should be removed in the image in consideration of the characteristics of human visibility as described above, and generates a histogram in the effective area based on a predetermined reference. Based on control.

  FIG. 2 is a block diagram illustrating a configuration example of the effective area control unit 21. As shown in the figure, the effective area control unit 21 includes a block distribution calculation unit 101 and a weight setting unit 102.

  Based on the input video signal, for example, the block distribution calculation unit 101 acquires screen data for one frame, and the image data for one screen is divided into a plurality of blocks each having a predetermined number of pixels. To divide. The block variance calculation unit 101 calculates the variance value of each block.

  A block having a large variance value can be said to be an image with many edges and inconspicuous noise (an image in which it is difficult for humans to visually recognize noise). A block having a large variance value is highly likely to be a portion with a large movement in the image, and can be said to be an image in which noise is not conspicuous.

  On the other hand, a block with a small variance value can be said to be an image with few edges and noticeable noise (an image in which a person can easily see noise). Also, a block with a large variance value is likely to be a portion with a small movement in the image, and can be said to be an image in which noise is conspicuous.

  The weight setting unit 102 is configured to set a weight coefficient corresponding to the block based on the variance value of the block calculated by the block variance calculation unit 101. For example, the weight setting unit 102 sets the weight coefficient to be smaller as the block variance value calculated by the block variance calculation unit 101 is larger, and the weight is set to be smaller as the block variance value calculated by the block variance calculation unit 101 is smaller. A large coefficient is set.

  Specifically, for example, a threshold value is stored in advance in the weight setting unit 102, and the variance value of the block calculated by the block variance calculation unit 101 is compared with the threshold value so that the weight coefficient is set. Good.

  As described above, a control signal including information in which a block and a weighting coefficient are associated with each other is output from the weight setting unit 102 and supplied to the histogram generation unit 32 as described above. Thereby, when generating the histogram, for example, the histogram generating unit 32 generates the histogram by multiplying the frequency of the difference value between the pixels of a certain block by the weighting coefficient associated with the block.

  As a result, the frequency of the histogram is high for a block of an image with a small variance value and noticeable noise with few edges, and the frequency of the histogram is low for a block of an image with no noticeable noise with many edges. Thus, for example, if there is a change in pixel brightness between frames in an image block with few edges, even if there is not much change in pixel brightness between frames in an image block with many edges, The possibility that a peak is formed on the right side increases.

  In this way, when the above-described noise amount calculation unit 33 has a change in pixel luminance between frames in an image block with few edges, the luminance of the pixel between frames in an image block with many edges. Even when there is not much change in, a relatively large amount of noise is calculated.

  Therefore, according to the present invention, in the case of an image with small motion or an image with few edges, a person feels a lot of noise, and in the case of an image with a large movement or an image with many edges, the person feels that there is little noise. It becomes possible to calculate the amount of noise corresponding to the characteristic of visibility. That is, as described above, the noise measurement unit 22 that has received the control signal from the effective region control unit 21 has a relatively large noise for a change in luminance value between frames in a portion with few edges in the image. Although the level is measured, a normal noise level can be measured for a portion with many edges in the image with respect to a change in luminance value between frames.

  Next, an example of noise level measurement processing by the noise level measurement apparatus 10 of the present invention will be described with reference to the flowchart of FIG.

  In step S11, the effective area control unit 21 executes an effective area control signal output process which will be described later with reference to FIG. Thereby, a control signal including the value of the weight coefficient corresponding to each block is generated.

  In step S12, the frame difference acquisition unit 31 acquires an inter-frame difference absolute value based on the input video signal. At this time, for example, as described above, the absolute difference between the luminance value of each pixel constituting the temporally previous frame image and the luminance value of each pixel constituting the temporally subsequent frame image is absolute. The value is calculated.

  In step S13, the histogram generation unit 32 generates a histogram, which is statistical data for calculating the noise amount, as described above, based on the data output from the frame difference acquisition unit 31 by the process of step S12. .

  In step S14, the histogram generation unit 32 weights the histogram frequency based on the control signal generated in the process of step S11. At this time, as described above, for example, the histogram generation unit 32 generates a histogram by multiplying the frequency of the difference value between the pixels of a certain block by the weighting coefficient associated with the block.

  In step S15, the noise amount calculation unit 33 calculates the noise amount of the video signal based on the histogram data supplied from the histogram generation unit 32 by the process of step S14.

  The noise amount calculated by the noise amount calculation unit 33 is normalized to a noise level by, for example, a predetermined standard, and is output as a measurement result of the noise level measuring device 10 in step S16.

  Here, a detailed example of the effective area control signal output processing in step S11 of FIG. 3 will be described with reference to the flowchart of FIG.

  In step S31, the block variance calculation unit 101 of the effective area control unit 21 calculates a block variance value based on the input video signal. At this time, as described above, the block distribution calculation unit 101 acquires, for example, image data of a screen for one frame based on the input video signal, and the image data for one screen is obtained by a predetermined number of pixels. Is divided into a plurality of blocks. The block variance calculation unit 101 calculates the variance value of each block.

  In step S32, the weight setting unit 102 of the effective area control unit 21 sets the weight coefficient of the block based on the variance value calculated in the process of step S31. At this time, for example, the weight setting unit 102 compares the threshold value stored in advance with the variance value of the block calculated in the process of step S31. When the variance value is less than the threshold value, the weight coefficient value is set to a value greater than “1”.

  In step S33, a control signal including the value of the weighting factor set in the process of step S32 and information for identifying the block in which the weighting factor is set is output.

  Thereafter, the processes in steps S12 to S16 described above are executed.

  In this way, the noise level is measured. By doing this, humans feel that there is a lot of noise in the case of images with small movements or images with few edges, and humans who feel that there is little noise in the case of images with large movements or images with many edges. The noise level can be calculated by calculating the amount of noise corresponding to the sensitivity characteristic. In addition, more natural image correction can be performed by controlling the noise reducer and the like using the measured noise level to remove noise from the image (video).

  Alternatively, in this way, it is possible to determine whether or not noise is included in the image based on the measurement result output from the noise level measurement device 10. For example, when a minute change is detected in the temporally previous image and temporally subsequent image, it is difficult to determine whether the change is noise. As described above, the measurement result output from the noise level measurement device 10 of the present invention can calculate the noise amount according to the characteristics of human visibility and measure the noise level. If image processing is performed on the basis of this, for example, a minute change that occurs in an image area with little motion or an image with few edges is processed as noise, and occurs, for example, in an area with a large motion or an image with many edges. Small changes can be processed as not being noise.

  In the above, characteristics of human visibility that people feel that there is a lot of noise in the case of images with small motion and images with few edges, and that people feel that there is little noise in the case of images with large movement and images with many edges In consideration of the above, the example in which the effective area control unit 21 detects the portion with few edges and sets the weighting coefficient has been described, but the weighting coefficient may be set by other methods.

  For example, in the image, the noise of a portion that is noticed by a person, such as a human face portion, is conspicuous even if it is minute, so the effective region control unit 21 detects the human face portion and sets the weighting coefficient. You may make it do.

  FIG. 5 is a block diagram illustrating another configuration example of the effective area control unit 21. In this example, the effective area control unit 21 includes a face image detection unit 111 and a weight setting unit 112.

  For example, the face image detection unit 111 acquires screen image data for one frame based on the input video signal, extracts a skin color region from the image, and uses a template or the like that is a standard face image. Then, it is determined whether the extracted skin color area is a face image area, and when it is determined that the extracted skin color area is a face image area, a square area including the skin color area is detected as a face image area. .

  For example, the face image detection unit 111 divides image data for one screen into a plurality of blocks each having a predetermined number of pixels, and flags indicating whether each block is a face image region or the like To the weight setting unit 112.

  The weight setting unit 112 is configured to set a weighting coefficient corresponding to a block determined to be a face image area by the face image detection unit 111. For example, the weight setting unit 112 sets a weight coefficient larger than “1” for a block in the face image area, and sets the weight coefficient to “1” for a block other than the block in the face image area. Has been made to set to.

  As described above, a control signal including information in which a block and a weighting coefficient are associated with each other is output from the weight setting unit 112 and supplied to the histogram generation unit 32 as described above. Thereby, when generating the histogram, for example, the histogram generating unit 32 generates the histogram by multiplying the frequency of the difference value between the pixels of a certain block by the weighting coefficient associated with the block.

  As a result, the frequency of the histogram is high for the face image block, and the frequency of the histogram is low for the blocks other than the face image block.

  Therefore, if the effective area control unit 21 is configured as shown in FIG. 5, the noise measurement unit 22 that has received the control signal from the effective area control unit 21 receives the human attention of the person as described above. The face part measures a relatively large noise level with respect to the change in luminance value between frames, but the part other than the human face measures the normal noise level with respect to the change in luminance value between frames. To be able to. In addition, if the noise reducer is controlled using the measured noise level in this way to remove noise from the image (video), natural image correction can be performed.

  Alternatively, the effective area control unit 21 may detect the dark part of the image and set the weighting coefficient. Even if the numerical values of the amount of noise calculated from each pixel value such as video signal and image data are the same, people feel that there is a lot of noise in the case of dark images, and people have less noise in the case of bright images feel.

  FIG. 6 is a block diagram showing still another configuration example of the effective area control unit 21. In this example, the effective area control unit 21 includes a weight setting unit 122.

  The weight setting unit 122 acquires, for example, image data of one frame of screen based on the input video signal, and divides the image data of one screen into a plurality of blocks each having a predetermined number of pixels. Then, the average value of the luminance of the pixels constituting these blocks is calculated. Then, for example, the weight setting unit 122 compares the calculated average value of luminance with a threshold value stored in advance, and if the average value of luminance is equal to or greater than the threshold value, sets the value of the weight coefficient to “1”, When the average luminance value is less than the threshold value, the value of the weighting coefficient is set to “1” or more.

  As described above, a control signal including information in which a block and a weighting coefficient are associated with each other is output from the weight setting unit 122 and supplied to the histogram generation unit 32 as described above. Thereby, when generating the histogram, for example, the histogram generating unit 32 generates the histogram by multiplying the frequency of the difference value between the pixels of a certain block by the weighting coefficient associated with the block.

  As a result, the histogram frequency is high for dark image blocks, and the histogram frequency is low for bright image blocks.

  Therefore, if the effective area control unit 21 is configured as shown in FIG. 6, the noise measurement unit 22 that has received the control signal from the effective area control unit 21 can detect a dark portion in the image as described above. Measures a relatively large noise level with respect to the change in luminance value between frames, but measures a normal noise level with respect to a change in luminance value between frames in a bright part of an image. can do. In addition, if the noise reducer is controlled using the measured noise level in this way to remove noise from the image (video), natural image correction can be performed.

  Alternatively, the weight setting unit 122 of the effective area control unit 21 may be configured to set the weight coefficient based on information supplied from another device. For example, the weight setting unit 122 may set the weighting coefficient in the same manner as described above based on the calculated amount of motion by a device that calculates the amount of motion for each pixel in the image. By doing so, for example, the noise measurement unit 22 measures a relatively large noise level with respect to a change in luminance value between frames in a portion where the motion is small in the image. For a large portion, a normal noise level can be measured with respect to a change in luminance value between frames.

  The series of processes described above can be executed by hardware, or can be executed by software. When the above-described series of processing is executed by software, a program constituting the software executes various functions by installing a computer incorporated in dedicated hardware or various programs. For example, a general-purpose personal computer 700 as shown in FIG. 7 is installed from a network or a recording medium.

  In FIG. 7, a CPU (Central Processing Unit) 701 executes various processes according to a program stored in a ROM (Read Only Memory) 702 or a program loaded from a storage unit 708 to a RAM (Random Access Memory) 703. To do. The RAM 703 also appropriately stores data necessary for the CPU 701 to execute various processes.

  The CPU 701, ROM 702, and RAM 703 are connected to each other via a bus 704. An input / output interface 705 is also connected to the bus 704.

  The input / output interface 705 includes an input unit 706 including a keyboard and a mouse, a display including a CRT (Cathode Ray Tube) and an LCD (Liquid Crystal display), an output unit 707 including a speaker, and a hard disk. A communication unit 709 including a storage unit 708, a network interface card such as a modem and a LAN card, and the like is connected. The communication unit 709 performs communication processing via a network including the Internet.

  A drive 710 is also connected to the input / output interface 705 as necessary, and a removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory is appropriately mounted, and a computer program read from them is loaded. It is installed in the storage unit 708 as necessary.

  When the above-described series of processing is executed by software, a program constituting the software is installed from a network such as the Internet or a recording medium such as a removable medium 711.

  The recording medium shown in FIG. 7 is a magnetic disk (including a floppy disk (registered trademark)) on which a program is recorded, which is distributed to distribute the program to the user separately from the apparatus main body. Removable media consisting of optical disks (including CD-ROM (compact disk-read only memory), DVD (digital versatile disk)), magneto-optical disks (including MD (mini-disk) (registered trademark)), or semiconductor memory It includes not only those configured by 711 but also those configured by a ROM 702 storing a program, a hard disk included in the storage unit 708, and the like that are distributed to the user in a state of being incorporated in the apparatus main body in advance.

  Note that the steps of executing the series of processes described above in this specification are performed in parallel or individually even if they are not necessarily processed in time series, as well as processes performed in time series in the order described. The processing to be performed is also included.

It is a block diagram which shows the structural example of the noise level measuring apparatus which concerns on one embodiment of this invention. It is a block diagram which shows the structural example of the effective area control part of FIG. It is a flowchart explaining the example of a noise level measurement process. It is a flowchart explaining an effective area | region control signal output process. It is a block diagram which shows another structural example of the effective area | region control part of FIG. It is a block diagram which shows another example of a structure of the effective area | region control part of FIG. And FIG. 16 is a block diagram illustrating a configuration example of a personal computer.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 10 Noise level measuring device, 21 Effective area control part, 22 Noise measurement part, 31 Frame difference acquisition part, 32 Histogram generation part, 33 Noise amount calculation part, 101 Block dispersion | distribution calculation part, 102 Weight setting part, 111 Face image detection part , 112 Weight setting unit, 122 Weight setting unit, 701 CPU, 711 Removable media

Claims (4)

A measuring device for measuring a noise level of a video signal,
Control information generating means for generating control information for each of a plurality of regions composed of a predetermined number of pixels in the image data in one frame of image data based on an input video signal;
For each of the plurality of regions in which the control information is generated based on the input video signal, the value of each pixel constituting image data for one frame earlier in time and one frame later in time Differential data acquisition means for acquiring the differential data of the values of the respective pixels constituting the image data;
The difference data acquisition is performed by setting the frequency of the difference value of the pixel value by multiplying the frequency of the difference value of the pixel value of each of the plurality of regions by a coefficient determined corresponding to the control information of the region. Histogram data generating means for generating histogram data of the difference data acquired by the means;
Noise amount calculating means for calculating the noise amount of the input video signal based on the histogram data generated by the histogram data generating means,
The control information generating means
Calculating the number of edges of the image in the region, the average value of the luminance of the pixels in the region, or a calculated value representing the amount of movement of the pixels in the region
A measurement device that generates the control information so that the value of the coefficient increases as the calculated value decreases. A measuring method of a measuring device for measuring a noise level of a video signal,
In the image data for one frame based on the input video signal, control information is generated for each of a plurality of regions composed of a predetermined number of pixels in the image data,
For each of the plurality of regions in which the control information is generated based on the input video signal, the value of each pixel constituting image data for one frame earlier in time and one frame later in time Each of the difference data of the values of the pixels constituting the image data of
The frequency of the difference value of each pixel value of the plurality of regions is multiplied by a coefficient determined corresponding to the control information of the region to set the frequency of the difference value of the pixel value, and the obtained Generating histogram data of the difference data based on the generated control information;
Calculating a noise amount of the input video signal based on the generated histogram data;
The number of edges of the image in the region, the average value of the luminance of the pixels in the region, or a calculated value representing the amount of motion of the pixels in the region is calculated,
The measurement method in which the control information is generated so that the value of the coefficient increases as the calculated value decreases. A program that causes a computer to measure the noise level of a video signal,
Computer
Control information generating means for generating control information for each of a plurality of regions composed of a predetermined number of pixels in the image data in one frame of image data based on an input video signal;
For each of the plurality of regions in which the control information is generated based on the input video signal, the value of each pixel constituting image data for one frame earlier in time and one frame later in time Differential data acquisition means for acquiring the differential data of the values of the respective pixels constituting the image data;
The difference data acquisition is performed by setting the frequency of the difference value of the pixel value by multiplying the frequency of the difference value of the pixel value of each of the plurality of regions by a coefficient determined corresponding to the control information of the region. Histogram data generating means for generating histogram data of the difference data acquired by the means;
Noise amount calculating means for calculating the noise amount of the input video signal based on the histogram data generated by the histogram data generating means,
The control information generating means
Calculating the number of edges of the image in the region, the average value of the luminance of the pixels in the region, or a calculated value representing the amount of movement of the pixels in the region
A program that functions as a measurement device that generates the control information so that the value of the coefficient increases as the calculated value decreases. A recording medium on which the program according to claim 3 is recorded.

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