JP2012130076A - Image processing method, image processing device, and imaging device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing device capable of making discrimination of whether an inputted image is a vivid scene or not closer to a human sense.SOLUTION: The image processing method comprises: an image acquisition step to acquire image data; a first correction step to correct saturation information of the image data based on at least one of hue information and brightness information of the image data; a discrimination step to discriminate, from saturation information corrected in the first correction step, whether an image of the image data is a vivid scene or not; and an output step to output a discrimination result in the discrimination step.

Description

  The present invention relates to an image processing method, an image processing apparatus, and an imaging apparatus that determine a scene of an input image and perform image processing according to the determined scene.

  2. Description of the Related Art Conventionally, there has been an image processing apparatus that determines an image scene and a subject type and performs image processing according to the determined scene (subject type).

  For example, Patent Document 1 discloses an image output apparatus that determines whether input image data is a vivid scene (subject) and outputs an image of a vivid scene with high resolution.

JP 2000-259372 A

  In the prior art disclosed in the above-mentioned patent document, it is determined whether the scene is vivid depending on whether or not the number of pixels having high saturation is greater than a predetermined threshold.

  However, depending on the color sensitivity of human beings and the distribution of subjects in the natural world, there are colors that are easy to perceive as vivid subjects and colors that are difficult to perceive depending on the color even with the same saturation. For this reason, if all the colors are processed with a uniform saturation threshold, it is determined that a vivid subject with grass on the entire screen is judged to be a vivid scene even if it is difficult to feel. there were.

  Accordingly, an object of the present invention is to provide an image processing apparatus capable of making it closer to a human sense to determine whether an input image is a vivid scene.

  In order to achieve the above object, an image processing method of the present invention is based on an image acquisition step of acquiring image data, and at least one of hue information and luminance information of the image data, as described in claim 1. From the first correction step for correcting the saturation information of the image data and the saturation information corrected in the first correction step, it is determined whether or not the image of the image data is a vivid scene. And a second correction step for correcting the saturation of the image data in accordance with the determination result in the determination step.

  The image processing apparatus according to the present invention, as set forth in claim 11, is based on at least one of acquisition means for acquiring image data and hue information and luminance information of the image data. A first correction unit that corrects information; a determination unit that determines whether the image of the image data is a vivid scene from the saturation information corrected by the first correction unit; and the determination unit And a second correction unit that corrects the saturation of the image data according to the determination result.

  The imaging device according to the present invention is the imaging device according to claim 12, wherein the image is picked up based on at least one of hue information and luminance information of the image data, and imaging means for imaging a subject and outputting image data. First correction means for correcting the saturation information of the data, and determination means for determining whether or not the image of the image data is a vivid scene from the saturation information corrected by the first correction means; And a second correction unit that corrects the saturation of the image data in accordance with the determination result of the determination unit.

  According to the present invention, it is possible to determine whether the scene is a vivid scene closer to a human sense by correcting the saturation according to the hue and luminance of the input image.

It is a block diagram which shows the structure of 1st Embodiment. It is a figure which shows the block division of an image signal. It is a flowchart which shows the process of the saturation correction | amendment part of 1st Embodiment. It is a graph which shows the characteristic of the saturation correction | amendment part of 1st Embodiment. It is a flowchart which shows the process of a scene discrimination | determination part. It is a graph which shows the characteristic of the scene discrimination | determination of a scene discrimination | determination part. It is a flowchart which shows the process of the saturation correction | amendment part of 2nd Embodiment. It is a figure which shows the example of a process of the saturation correction | amendment part of 2nd Embodiment. It is a graph which shows the characteristic of the saturation correction | amendment part of 2nd Embodiment. It is a block diagram which shows the structure of 3rd Embodiment. It is a flowchart which shows the process of the saturation correction | amendment part of 3rd Embodiment. It is a graph which shows the characteristic of the saturation correction | amendment part of 3rd Embodiment.

(First embodiment)
Hereinafter, an imaging apparatus as an example of an image processing apparatus according to the first embodiment will be described with reference to FIGS.

  FIG. 1 is a block diagram illustrating a configuration of an imaging apparatus that has a function of detecting a scene of a captured image and performs image correction processing according to the scene.

  Each block in FIG. 1 will be described. In FIG. 1, reference numeral 101 denotes a lens that forms an image of a luminous flux of a subject. Reference numeral 102 denotes an aperture stop that is used to guide the light flux from the lens to the image sensor. An image sensor 103 photoelectrically converts an incident light beam and outputs it as an image signal. An auto gain control amplifier (AGC) 104 amplifies the signal from the image sensor 103 to an appropriate level.

  A luminance / color signal generation unit 105 converts a signal generated by the image sensor 103 into a luminance signal (Y) and a color signal (R, G, B). A white balance amplifying unit 106 amplifies the color signals (R, G, B) output from the luminance / color signal generation unit 105 according to the white balance gain, and amplifies the color signals (R ′, G ′, B ′). Is generated. A color difference signal generation unit 107 generates color difference signals (R′−Y, B′−Y). Reference numeral 108 denotes a color difference signal correction unit that performs correction such as applying gain to the color difference signal, and 109 denotes an encoder that converts the color difference signal into a standard television signal or the like.

  A signal dividing unit 110 divides the luminance signal (Y) and the color difference signals (RY, BY) into predetermined small blocks. Reference numeral 111 denotes a hue / saturation calculation unit that calculates the hue and saturation signals (Hue, Chroma) from the color difference signals (RY, BY), and 112 denotes a camera control unit that controls the entire imaging system. Although not shown, it is possible to send an instruction to each unit in the imaging apparatus to perform processing. 113 is a scene discriminating unit that discriminates the scene of the input image, and 114 is a chroma correction unit that corrects the chroma value.

  Next, the shooting operation of the image pickup apparatus in FIG. 1 will be described. The light incident on the image sensor 103 is photoelectrically converted, amplified to an appropriate level by the AGC amplifier 104, and then output to the luminance / color signal generation unit 105. The luminance / color signal generation unit 105 generates a luminance signal (Y) and a color signal (R, G, B) from the image signal formed by the image sensor 103, and among these, the color signal (R, G, B) is generated. Output to the white balance amplifier 106.

  The white balance amplification unit 106 amplifies the color signals (R, G, B) based on the white balance gain calculated by the camera control unit 112, and the amplified color signals (R ′, G ′, B ′) are color-differenced. The signal is output to the signal generator 107. The color difference signal generation unit 107 generates color difference signals (RY, BY) from the color signals (R ′, G ′, B ′), and outputs them to the color difference signal correction unit 108 and the signal division unit 110. The color difference signal correcting unit 108 corrects the color difference signals (R−Y, B−Y) by applying a gain G (G is equal to or greater than 1. The gain intensity will be described later) calculated by the camera control unit 112. . That is, the corrected color difference is (R−Y) ′ = G × (R−Y) and (B−Y) ′ = G × (B−Y). Further, the corrected color difference signals (R−Y) ′ and (B−Y) ′ are output to the encoder 109.

  The encoder 109 generates and outputs a standard television signal such as NTSC from the luminance signal (Y) and the color difference signals (R−Y) ′ and (B−Y) ′.

  The above is the basic processing at the time of imaging. Among the processes described above, the flowchart of FIG. 1B shows an outline of a process for detecting a scene of a captured image and performing an image correction process corresponding to the scene. This process is performed by the camera control unit 112 or by each unit according to an instruction from the camera control unit 112.

  In step S101, the image data output from the color difference signal generation unit 107 is acquired by the color difference signal correction unit 108 (image acquisition step). In step S102, a saturation weight determination process for weighting the saturation obtained from the image data in accordance with the characteristics of the image data is performed (first correction step) so that a determination closer to a human sense can be made. In step S103, a vividness discrimination process is performed in which it is determined whether or not the image of the obtained image data is a vivid scene using the saturation information and luminance information after weighting (discrimination step). . In step S104, a vivid correction process for correcting the saturation of the image data based on the determination result in step S103 is performed (second correction step), and the process ends. Details of the saturation weight determination process, the vividness determination process, and the vividness correction process will be described later.

  Here, in the present embodiment, the image data used for the scene discrimination result is output by reflecting the discrimination result, but the invention is not particularly limited to this. In other words, it is naturally possible to reflect the correction processing corresponding to the determination result for a certain frame (image data) in the subsequent frames. In addition, the scene is identified for the first time when a multi-frame vivid scene discrimination result continues, or the scene is identified when the ratio of vivid scenes is high in multiple frames. It is also possible to specify a scene. At this time, it is conceivable that the correction process according to the determination result is reflected in the plurality of frames and the subsequent frames.

  The situation that is specifically assumed is a situation in which processing is performed on captured image data (frames) in an imaging apparatus capable of capturing a still image or an information processing apparatus such as a PC that performs image processing on image data. is there. In addition, in an information processing apparatus such as an imaging apparatus capable of live view display or moving image shooting or a PC that performs image processing on a moving image, the above-described processing over a plurality of frames is assumed.

  In this embodiment, the saturation correction is applied to the image data using the determination result output by the scene determination unit 114, but the method of using the determination result is not limited to this. For example, when the determination result is displayed on a display means (not shown) to inform the user or save the image data, information corresponding to the determination result is attached to a header or the like, and the image data is captured after the storage. You can also specify the scene. Even if one correction is taken, the vividness may be enhanced by correcting other than the saturation. Such processing includes, for example, correction for increasing luminance and contour enhancement processing.

  Next, image signal characteristic analysis processing will be described. The signal dividing unit 110 divides the image signal into a plurality of blocks (8 × 8 blocks) as shown in FIG. 2 and averages the luminance signal (Y) and color difference signals (RY, BY) for each block. The value is calculated and output to the hue / saturation calculation unit 111.

  The hue / saturation calculation unit 111 acquires the hue information / saturation information of each block from the color difference signals (RY, BY) by calculation. Hue (Hue) and saturation (Chroma) are calculated based on the following equations.

  The hue / saturation calculation unit 111 outputs the calculated hue (Hue) and saturation (Chroma) of each block to the saturation correction unit 114. Further, the signal dividing unit 110 outputs the calculated luminance (Y) of each block to the saturation correction unit 114.

  The saturation correction unit 114 corrects the saturation in a direction of increasing the saturation by applying a weight to the saturation (Chroma) based on the hue (Hue) and luminance (Y) of each input block. A processing flow of the saturation correction unit 114 will be described with reference to FIG. 3 (first correction step).

  In the process of FIG. 3, a loop process is performed on the 8 × 8 block shown in FIG. That is, the processing in steps S301 to S303 is performed for all blocks in FIG.

  In step S301, the upper and lower limits of the saturation weight are determined based on the hue (Hue) of the block. This process will be described with reference to FIG. FIG. 4A is a diagram showing the relationship between hue (Hue) and saturation weight upper and lower limits. In FIG. 4, L401 indicates the characteristic of the weight upper limit value, and L402 indicates the characteristic of the weight lower limit value. From the characteristics shown in FIG. 4, it is possible to calculate the weight and upper limit for each hue value. For example, when the hue is H1 (red), the weight lower limit is 1.2 and the weight upper limit is 1.4. As shown in the figure, even if the other parameters other than the hue are the same, the human sensation tends to feel more vivid when the hue is red than when the hue is blue. In the present embodiment, in order to deal with this characteristic, correction is performed by changing the weight applied to the saturation according to the hue even under the same conditions. A specific weighting method can be defined by the length of the wavelength or the like, but in the present embodiment, the weight for each hue is set empirically in light of human perceptual characteristics.

  Returning to FIG. 3, in step S302, the saturation weight is determined based on the upper and lower weight values calculated in step S303 and the block luminance (Y). This process will be described with reference to FIG. FIG. 4B is a diagram showing the relationship between the luminance (Y) of the block and the upper and lower saturation weights. In FIG. 4B, L403 indicates the characteristics of block luminance and weight. The weight upper limit value W1 is the weight upper limit value calculated in step S301, and the weight lower limit value W2 is the weight lower limit value calculated in step S301. For example, as in the above example, when the hue is H1 in FIG. 4A, the weight upper limit value W1 in FIG. 4B is 1.4 and the lower limit value W2 is 1.2. At this time, if the block luminance is Y1, the final weight is W1 = 1.4. As shown in the figure, even if other parameters other than the brightness are the same, the human sense tends to feel brighter in the case of an image with high brightness than in the case of an image with low brightness. To accommodate this characteristic, under the same conditions, an image with a higher luminance (first block with a first luminance) has a lower luminance than that image (a second block with a second luminance). ), The weight is set in the direction of increasing the saturation and correction is performed.

  Returning to FIG. 3, in step S303, the determined saturation weight is multiplied by the saturation (Chroma) to calculate the corrected saturation. In the above example, since the weight is 1.4, the corrected block saturation (Chroma ') = 1.4 × Chroma.

  The above is the saturation correction processing in the saturation correction unit 114. The above saturation correction processing is performed on all blocks shown in FIG. 2, and the corrected saturation (Chroma ′) is output to the scene determination unit 113. Further, the luminance (Y) of each block is output from the signal dividing unit 110, and the hue (Hue) of each block is output from the hue / saturation calculating unit 111 to the scene determination unit 113.

  The scene determination unit 113 determines whether the shot scene is a vivid scene based on the input luminance (Y), hue (Hue), and corrected saturation (Chroma ′) for each block. . Hereinafter, the flow of the vividness determination process of the scene determination unit 113 will be described with reference to FIG. 5 (determination step).

  In FIG. 5, in step S501, the corrected saturation (Chroma ') calculated by the saturation correction unit 114 is averaged over all the blocks in FIG. 2, and the average saturation is calculated.

  In step S502, the number of blocks having a corrected saturation (Chroma ') equal to or greater than a predetermined threshold among all the blocks in FIG. 2 is counted.

  In step 503, it is determined whether the scene is a vivid scene based on the average saturation of all blocks obtained in step S501 and the number of blocks in which the saturation obtained in step S502 is equal to or greater than a threshold. FIG. 6 is a diagram showing a bright scene determination criterion with respect to the average saturation value and the number of blocks having a saturation equal to or greater than a threshold value. As shown in FIG. 6, the number of blocks whose average saturation is higher than the average saturation threshold Ct (sixth threshold) and whose saturation is equal to or greater than the threshold (fourth threshold) is higher than the threshold At (fifth threshold). If it is too large, it is determined that the scene is vivid.

  The above is the process of the scene determination unit 113. Information about whether or not the scene is a vivid scene determined by the scene determination unit is output to the camera control unit 112.

  The camera control unit 112 controls the parameters of the color difference signal correction unit 108 based on information on whether or not the scene is a vivid scene determined by the scene determination unit 113 (second correction step). In the present embodiment, the color difference gain G of the above-described color difference signal correction unit 108 is controlled. There are parameters G1 and G2 as the color difference gain G, and G1> G2 ≧ 1. Here, if it is determined that the scene is a vivid scene, the color difference gain is set to G1, and if it is determined that the scene is not a vivid scene, the color difference gain is set to G2. That is, when it is determined that the scene is vivid, the gain for the color difference signal is increased as compared with the case where it is determined that the scene is not vivid, thereby correcting the image with higher saturation and enhanced vividness.

  As described above, in this embodiment, in the image processing apparatus that determines whether or not the scene is vivid and controls image processing according to the determination result, the saturation, luminance, and hue of the image signal are calculated, and the hue is calculated. The saturation was corrected based on the luminance information. In addition, it is configured to determine whether or not the scene is vivid using the corrected saturation.

  As a result, the saturation value can be corrected in accordance with human senses, and vivid scene discrimination closer to human senses can be performed.

  In this embodiment, the saturation is weighted based on the luminance and the hue. However, the saturation may be weighted based on only the information on the hue or the luminance.

  In the present embodiment, the hue / saturation is calculated from the color difference signal, but the method of calculating the hue / saturation is not limited to this. For example, the hue / saturation in the L * a * b * space may be calculated after being once converted into another space such as the L * a * b * space.

  In this embodiment, the example in which the signal dividing unit 110 divides the image signal into 8 × 8 blocks has been described, but any number of divisions may be used. Further, a configuration may be adopted in which the saturation is weighted in units of pixels.

  In the present embodiment, the case where the gain applied to the color difference signal is controlled based on the determination result of whether or not the scene is vivid is described. However, the control for correcting the color signal or the luminance signal based on the scene determination result is described. Any control can be performed.

  In the present embodiment, whether or not a scene is vivid is determined based on two pieces of information: an average saturation value and the number of blocks whose saturation is equal to or greater than a threshold value. However, the method for discriminating a vivid scene is not limited to this, and any configuration may be adopted as long as the vivid scene is discriminated using saturation information corrected by hue and luminance.

  In the present embodiment, the determination is made based on the binary value of whether or not the scene is vivid, but it may be calculated with multiple values such as the vividness. In this case, the higher the average saturation is, the higher the degree of vividness is. Based on the calculated vividness, the correction intensity of the signal of the color difference signal correcting unit 108 is controlled (the higher the vividness, the higher the gain applied to the color difference signal).

  In the present embodiment, the processing for increasing the saturation and enhancing the vividness of the image data determined to be a vivid scene has been described. However, the present invention is not limited to this, and conversely for the vivid scene. It can also be applied to processing that reduces saturation and suppresses vividness. In this case, for example, the gain may be set such that G1 <G2 ≦ 1.

(Second Embodiment)
Hereinafter, an imaging device according to the second embodiment of the present invention will be described with reference to FIGS. In the second embodiment, an example will be described in which the saturation is corrected according to the color area in addition to the hue and luminance described in the first embodiment.

  Since the block configuration of the imaging apparatus according to the present embodiment is the same as that shown in FIG. In the present embodiment, the processing contents in the saturation correction unit 114 in FIG. 1 are different from those in the first embodiment. Specifically, the weight calculated by the saturation correction unit 114 is changed depending on the ratio of the color to the image data, that is, the area.

  A processing flow of the saturation correction unit 114 is shown in FIG. 7 (first correction step).

  In FIG. 7, in step S701, a hue histogram is generated. The hue histogram is obtained by counting the frequency for each hue in all blocks shown in FIG. FIG. 8A shows an example of a hue histogram in which hues are divided in units of 10 degrees. In FIG. 8, the horizontal axis indicates hue, and the vertical axis indicates frequency.

  In step S702, the hue of the peak with the highest frequency is detected from the generated hue histogram. In the example of FIG. 8A, the hue Hp (20 to 30 degrees) is the peak hue. Cp represents the frequency of the hue Hp.

  In step S703, it is determined whether the frequency of the peak hue is equal to or greater than a threshold value (the area in the peak hue image is equal to or greater than the threshold value). In the example of FIG. 8A, it is determined whether the frequency Cp of the peak hue Hp is equal to or greater than a threshold (first threshold). If it is greater than or equal to the threshold, the process proceeds to step S704. If it is less than the threshold, the process proceeds to step S707.

  In step S704, the density of the block having the peak hue is calculated.

  A method for calculating the degree of congestion will be described with reference to FIGS. First, with respect to all the blocks, it is determined whether or not the block satisfies the peak hue Hp (20 degrees to 30 degrees in the example of FIG. 8A), and the blocks satisfying the peak hue Hp are labeled. Next, it is confirmed whether the upper, lower, left and right blocks of the block with the peak hue are filled with the hue Hp. If the hue Hp is satisfied, the number of blocks is counted. This process will be specifically described with reference to FIG. In FIG. 8B, the blocks filled with gray satisfy the hue Hp. For example, for the block 801 that satisfies the hue Hp, it is confirmed whether the hue Hp is satisfied for the surrounding 801 (upper) (lower) (left) (right). In this case, the count number of the block 801 is 2 because 801 (top) and 801 (left) satisfy the hue Hp. Similarly, for the blocks satisfying all the hues Hp, the number of blocks satisfying the hues Hp on the top, bottom, left and right is counted. The numerical values described in FIG. 8B are obtained by counting the number of blocks that satisfy the hue Hp in the vicinity of all the blocks that satisfy the hue Hp. The sum of these numbers is the density. In the case of the example of FIG. 8B, the density is 4. FIG. 8C is an example similar to FIG. 8B, and the density in this case is 32. Thus, the density increases as the blocks satisfying the hue Hp are solidified.

  Returning to FIG. 7, in step S <b> 705, it is determined whether or not the calculated density is greater than or equal to a threshold (second threshold). If it is equal to or greater than the threshold value, the process proceeds to step S706, and if it is less than the threshold value, the process proceeds to step S707.

  In step S706, the saturation weight correction degree Wc is calculated based on the area of the color that satisfies the hue Hp. The area of the color that satisfies the hue Hp is the frequency Cp (FIG. 8A) of the hue histogram.

  The calculation of the saturation weight correction degree Wc will be described. First, the average luminance Ya of the block that satisfies the hue Hp is calculated. The weight correction degree when the area is maximum is determined by the calculated average luminance Ya. FIG. 9A is a graph showing the relationship between the weight correction degree and the luminance when the area is maximum. According to this graph, the weight correction degree at the time of maximum area is calculated from the average luminance Ya of the hue Hp region. In the example of FIG. 9A, the weight correction degree at the maximum area when the luminance is Y1 is 1.2, and the weight correction degree at the maximum area when the luminance is Y2 is 0.95. If the average luminance Ya is equal to or greater than the threshold Y0 (third threshold), the weight correction degree is 1 or more, and the weight correction is performed so as to increase the saturation. On the contrary, if the average luminance Ya is less than the threshold value Y0, the weight correction degree is less than 1, and the weight correction is performed so as to lower the saturation.

  Next, the final weight correction degree Wc is determined based on the frequency (area) Cp of the region satisfying the hue Hp and the weight correction degree when the area is maximum. FIG. 9B is a graph showing the relationship between the weight correction degree and the area when the area is maximum. The final weight correction degree Wc is calculated according to the graph of FIG.

  In FIG. 9B, 901 shows a graph when the weight correction degree at the maximum area is 1.2, and 902 shows a graph when the weight correction degree at the maximum area is 0.95. When the area is the minimum, the correction degree of the weight is 1.0, and when the area is the maximum (entire screen), the correction degree is the value calculated in FIG.

  Returning to FIG. 7, in step S707, saturation weight correction based on area is not performed. That is, the saturation weight correction degree Wc = 1.0.

  In step 708, loop processing is performed on all the blocks shown in FIG. That is, the processes in steps S709 to S713 are performed on all blocks.

  Steps S709 and S710 are the same as steps S302 and S303 described in FIG. 3 of the first embodiment. That is, the weight Wf is determined by the hue and luminance for each block.

  In step S711, it is determined whether the hue of the processing target block is included in the peak hue Hp. If it is a block of peak hue Hp, the process proceeds to step S712, and if it is not a block of peak hue, the process proceeds to step S713.

  In step S712, the weight Wf calculated in step S710 is corrected. Specifically, the weight Wf is corrected by multiplying the weight Wf by the weight correction degree Wc based on the area determined in steps S706 and S707 (Wf = Wc × Wf).

  In step S713, the saturation value is corrected by multiplying by the weight Wf. This process is the same as the process 304 in FIG. 3 of the first embodiment.

  The above is the processing of the saturation correction unit 114 in the present embodiment.

  As described above, in the present embodiment, the saturation, luminance, hue, and color area of the image signal are calculated, and the saturation is corrected based on the information on the hue, luminance, and color area. It is configured to determine whether or not the scene is vivid using saturation. The reason for controlling in this way is that the area effect is that for a bright color, the larger the area, the brighter and more saturated it feels, and for the dark color, the larger the area, the darker and the less saturated the color appears. Is to reflect.

  As a result, the saturation value can be corrected in accordance with human visual characteristics, and vivid scene discrimination closer to human senses can be performed.

  In the above-described embodiment, the example in which the weight correction degree Wc is controlled according to the density and the area of a block of a certain hue has been described. However, the weight is corrected based on information on either the density or the area. Control may be performed.

  In the above-described embodiment, correction is performed only by the area of the peak hue Hp. However, a saturation value may be corrected by an area having the same hue for a block having other than the peak hue.

  In the above-described embodiment, the configuration in which the weight is corrected by the area has been described. However, as in the modification in the first embodiment, the saturation may be directly corrected based on the area information.

(Third embodiment)
Hereinafter, an imaging apparatus according to the third embodiment will be described with reference to FIGS.

  In the third embodiment, a mode in which the saturation is corrected according to the amount of movement of the subject will be described in addition to the hue and luminance described in the first embodiment.

  FIG. 10 is a block diagram illustrating a configuration of the imaging apparatus according to the present embodiment. In FIG. 10, the same reference numerals as those in FIG. In the present embodiment, an evaluation value memory 1001 and a motion amount detection unit 1002 are added to the configuration of FIG.

  Next, a processing flow of the imaging apparatus illustrated in FIG. 10 will be described. The flow from capturing an image to outputting it by the encoder 109 is the same as in the first embodiment. Also, the scene determination unit 113 determines whether or not the scene is a vivid scene, and the camera control unit 112 controls the parameters of the color difference signal correction unit 108 according to the determination result, as in the first embodiment. Therefore, detailed description is omitted.

  Similarly to the first embodiment, the signal dividing unit 110 calculates an average value of the luminance signal (Y) and the color difference signals (RY, BY) for each block, and a hue / saturation calculating unit as an evaluation value. To 111. Further, the luminance signal (Y) is output to the evaluation value memory 1001 and the motion amount detection unit 1002. The evaluation value memory 1001 stores the luminance signals (evaluation values) of all blocks output from the signal dividing unit 110. The luminance signal (evaluation value) is stored in the evaluation value memory 1001 at predetermined time intervals, and the evaluation value memory 1001 records the luminance signal (evaluation value) for a predetermined frame.

  The motion amount detection unit 1002 calculates a motion amount in units of blocks from the current luminance signal output from the signal dividing unit 110 and the past luminance signal stored in the evaluation value memory 1001. Specifically, for each block, a temporal dispersion value of the luminance signal at a certain time is calculated, and this temporal dispersion value is used as the amount of motion. The motion amount detection unit 1002 outputs the calculated motion amount information of all blocks to the saturation correction unit 114 (motion amount detection step).

  The saturation correction unit 114 corrects the saturation value based on the hue, luminance, and amount of motion. A processing flow of the saturation correction unit 114 is shown in FIG. 11 (first correction step).

  In FIG. 11, in step S1101, loop processing is performed on all the blocks shown in FIG. That is, the processing in steps S1102 to S1105 is performed on all blocks.

  Steps S1101 and S1102 are the same as steps S302 and S303 described in FIG. 3 of the first embodiment. That is, the weight Wf is determined by the hue and luminance for each block.

  In step S1104, the weight Wf is corrected based on the amount of motion. FIG. 12 shows the relationship between the motion amount and the weight correction rate Wc. As shown in FIG. 12, the correction is performed so that the weight becomes smaller as the motion amount of the block is larger. The final weight is determined by multiplying the weight Wf by the calculated weight correction rate Wc (Wf = Wc × Wf).

  In step S1105, the saturation value is corrected by multiplying by the weight Wf. This process is the same as the process 304 in FIG. 3 of the first embodiment.

  The above is the processing of the saturation correction unit 114. As described above, in the present embodiment, the saturation value is corrected not only by the hue and luminance but also by the amount of motion. The reason for controlling in this way is that when the subject or the movement of the camera is large, it is difficult to recognize a subject with the same saturation value as a bright subject. Therefore, by correcting the saturation value according to the amount of motion, it becomes possible to perform a vivid scene discrimination closer to a human sense.

  In this embodiment, the saturation signal is corrected based on the amount of motion of the image signal so that it is difficult to determine vivid in a scene with a lot of motion. It is also possible to take the following configuration.

  For example, a configuration may be adopted in which the threshold for vivid discrimination (FIG. 6) of the scene discrimination unit 113 is changed based on the motion information. In this case, the higher the amount of motion, the higher the average saturation threshold value Ct and the block number threshold value At whose saturation is equal to or greater than the threshold value in FIG. This makes it difficult to distinguish a scene with a large movement from a bright scene.

  In the present embodiment, any configuration may be used as long as the amount of motion is obtained. For example, the amount of motion may be obtained using not only the luminance signal but also the color signal.

  In the present embodiment, the motion amount in units of blocks is calculated. However, a configuration in which the motion amount in the entire image is calculated may be used. In addition, optical system information of the imaging apparatus such as zoom may be acquired and used for motion amount calculation.

(Other embodiments)
The object of the present invention can also be achieved as follows. That is, a storage medium in which a program code of software in which a procedure for realizing the functions of the above-described embodiments is described is recorded is supplied to the system or apparatus. The computer (or CPU, MPU, etc.) of the system or apparatus reads out and executes the program code stored in the storage medium.

  In this case, the program code itself read from the storage medium realizes the novel function of the present invention, and the storage medium and program storing the program code constitute the present invention.

  Examples of the storage medium for supplying the program code include a flexible disk, a hard disk, an optical disk, and a magneto-optical disk. Further, a CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD-R, magnetic tape, nonvolatile memory card, ROM, or the like can also be used.

  Further, by making the program code read by the computer executable, the functions of the above-described embodiments are realized. Furthermore, when the OS (operating system) running on the computer performs part or all of the actual processing based on the instruction of the program code, the functions of the above-described embodiments are realized by the processing. Is also included.

  Furthermore, the following cases are also included. First, the program code read from the storage medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer. Thereafter, based on the instruction of the program code, the CPU or the like provided in the function expansion board or function expansion unit performs part or all of the actual processing.

  In the present embodiment, an imaging apparatus has been described as an example of an image processing apparatus to which the present invention can be applied. However, the present invention is not limited to this. It can be applied to both imaging devices that can shoot still images and moving images, and can be applied to image forming devices such as printers that acquire image data from the outside for processing, and information processing devices such as personal computers. The present invention is applicable.

DESCRIPTION OF SYMBOLS 101 Lens 102 Diaphragm 103 Image pick-up element 104 AGC amplifier 105 Luminance / color signal generation part 106 WB amplification part 107 Color difference signal generation part 108 Color difference signal correction part 109 Encoder 110 Signal division part 112 Camera control part 113 Scene discrimination part 114 Saturation correction part

Claims (13)

An image acquisition step for acquiring image data;
A first correction step of correcting saturation information of the image data based on at least one of hue information and luminance information of the image data;
A determination step of determining whether or not the image of the image data is a vivid scene from the saturation information corrected in the first correction step;
An image processing method comprising: an output step of outputting a discrimination result in the discrimination step.   The image processing method according to claim 1, further comprising a second correction step for correcting the saturation of the image data in accordance with the determination result output in the output step.   In the first correction step, the image data is divided into a plurality of blocks, and the saturation information is corrected for each block. At this time, a weight corresponding to the hue information for each block is set for each block. The image processing method according to claim 1, wherein the image processing method is applied to saturation information.   In the first correction step, the image data is divided into a plurality of blocks and the saturation information is corrected for each block. At this time, the first block having the first luminance is the first block. 4. The image processing method according to claim 1, wherein the image processing method is corrected in a direction of increasing saturation as compared with the second block having the second luminance lower than the luminance. 5.   In the first correction step, if there is a hue whose proportion in the image data is higher than the first threshold, and the area where the hue is dense in the image is larger than the second threshold, the density is increased. The image processing method according to claim 1, wherein the correction is performed in accordance with the area that is present. In the first correction step, when there is a hue whose proportion in the image data is higher than the first threshold, and the area where the hue is dense in the image data is larger than the second threshold,
When the average brightness of the image data is higher than a third threshold, correction is performed in the direction of increasing the saturation of the image data,
The image processing method according to claim 5, wherein when the average luminance of the image data is lower than a third threshold value, correction is performed in a direction of decreasing the saturation of the image data. A motion amount detection step of detecting a motion amount of a subject in the image data from the plurality of image data acquired in the acquisition step;
7. The correction according to claim 1, wherein in the first correction step, the saturation is corrected in a direction in which the saturation is decreased as the amount of motion detected in the motion amount detection step is larger. Image processing method.   In the determining step, the entire image of the image data is divided into a plurality of blocks, and when the number of blocks having a saturation greater than the fourth threshold is greater than the fifth threshold, it is determined that the scene is vivid. The image processing method according to claim 1, wherein:   9. The image processing method according to claim 1, wherein in the determination step, when the average saturation of the image data is higher than a sixth threshold, it is determined that the scene is a vivid scene. .   A computer-executable program in which a procedure of the image processing method according to any one of claims 1 to 9 is described.   A computer-readable storage medium storing a program in which the procedure of the image processing method according to claim 1 is described. Acquisition means for acquiring image data;
First correction means for correcting the saturation information of the image data based on at least one of hue information and luminance information of the image data;
Discrimination means for discriminating whether or not the image of the image data is a vivid scene from the saturation information corrected by the first correction means;
And an output unit that outputs a determination result of the determination unit. Imaging means for imaging a subject and outputting image data;
First correction means for correcting the saturation information of the image data based on at least one of hue information and luminance information of the image data;
Discrimination means for discriminating whether or not the image of the image data is a vivid scene from the saturation information corrected by the first correction means;
And an output unit that outputs a determination result of the determination unit.