JP2018092594A - Image processing apparatus, image processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide processing for emphasizing gloss of an object in consideration of a surface shape of the object.SOLUTION: An image processing apparatus includes: first acquisition means of acquiring shape information representing the shape of the surface of an object, and reflection characteristic information representing reflection characteristics of the object; second acquisition means of acquiring point-of-view information relating to a point of view for viewing the object, and light source information relating to a light source which irradiates the object with light; emphasizing means which emphasizes light reflection intensity of the object, on the basis of the reflection characteristic information, the point-of-view information, the light source information, and the shape information, so as to increase a degree of emphasis as flatness of the shape is higher in image data representing the object; and output means of outputting the image data which represents the object with the light reflection intensity emphasized by the emphasizing means.SELECTED DRAWING: Figure 2

Description

  The present invention relates to an image processing technique for the gloss of an object in an image.

  Conventionally, a technique for adding gloss to an object in an image is known. Patent Document 1 discloses a technique for adding a highlight to an arbitrary position in an object to be rendered by setting a light source position so that specular reflection light is directed toward a viewpoint in 3D computer graphics (3DCG). ing. In this technique, an arbitrary range of an object is specified, and highlights are added by setting the light source position so that the reflected light in the range is uniformly specularly reflected.

  On the other hand, a technique for reproducing fine irregularities on an object surface with CG or the like has begun to spread. An object having a fine concavo-convex shape on the surface has a finer change in the normal direction of the reflecting surface in accordance with the change in the concavo-convex shape than an object having a smooth surface. This fine change in the normal direction gives a fine change to the specular reflection direction of light, and consequently the intensity of reflected light observed from the viewpoint position. This variation appears as an object-specific texture. For example, it is known that the above-mentioned texture appears in a metallic material including minute metal flakes, a material subjected to a satin finish, or the like.

JP-A-6-111028

  When a highlight is added to an object that is to reproduce the texture of a metallic material or the like as described above using the technique disclosed in Patent Document 1, the reflected light at the highlight portion is uniformly specularly reflected as described above. It becomes light. For this reason, the above-described minute fluctuation of the intensity of the reflected light does not occur in the highlight portion. As a result, there is a problem that the texture specific to the object in the highlight portion is impaired.

  SUMMARY An advantage of some aspects of the invention is that it provides a process for enhancing the gloss of an object in consideration of the shape of the object surface.

  In order to solve the above-described problem, an image processing apparatus according to the present invention is configured to obtain first shape acquisition means for acquiring shape information representing a shape of an object surface and reflection characteristic information representing a reflection characteristic of the object, and viewing the object. A second acquisition unit configured to acquire viewpoint information relating to a viewpoint and light source information relating to a light source that applies light to the object; and the object based on the reflection characteristic information, the viewpoint information, the light source information, and the shape information. In the image data to represent, the enhancement means for enhancing the reflection intensity of the light of the object so that the enhancement degree is increased as the flatness of the shape is higher, and the object whose reflection intensity of the light is enhanced by the enhancement means. Output means for outputting the image data to be expressed.

  According to the present invention, the gloss of the object can be enhanced in consideration of the shape of the object surface.

The figure which shows the hardware constitutions of the image processing apparatus 100 The block diagram which shows the function structure of the image processing apparatus 100 Flowchart showing a flow of a series of processing in the image processing apparatus 100 The flowchart which shows the flow of the process in the production | generation part 204. The figure which shows an example of a shape feature-value Diagram showing an example of a feature image The figure which shows an example of a base image Diagram showing an example of output image Diagram showing an example of reflection

  Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings.

[Embodiment 1]
In the present embodiment, processing for changing the degree of enhancement for enhancing glossiness is performed according to the feature of the shape of the object surface to be rendered. This will be described in detail below.

<Hardware Configuration of Image Processing Apparatus 100>
FIG. 1 is a diagram illustrating a hardware configuration example of the image processing apparatus 100. The image processing apparatus 100 includes a CPU 101, ROM 102, RAM 103, hard disk drive (HDD) 104, HDD interface (I / F) 105, input I / F 106, output I / F 107, and system bus 108. The CPU 101 executes programs stored in the ROM 102 and the HDD 104 using the RAM 103 as a work memory, and controls each unit to be described later via the system bus 108. The HDD I / F 105 is an interface such as serial ATA (SATA) for connecting a secondary storage device such as the HDD 104 or an optical disk drive. The CPU 101 can read data from the HDD 104 and write data to the HDD 104 via the HDD I / F 105. Further, the CPU 101 can expand the data stored in the HDD 104 to the RAM 103, and similarly, can store the data expanded in the RAM 103 in the HDD 104. The CPU 101 can execute the data expanded in the RAM 103 as a program. The input I / F 106 is a serial bus interface, such as a USB, for connecting an input device 109 such as a keyboard, a mouse, and a 3D scanner. The CPU 101 can read various data from the input device 109 via the input I / F 106. The output I / F 107 is a serial bus interface such as USB or IEEE for connecting an output device 110 such as a monitor or a printer. The CPU 101 can send data to the output device 110 via the output I / F 107 to execute display and recording. If a bidirectional communication interface such as USB or IEEE is used, the input I / F 106 and the output I / F 107 can be combined into one.

<Functional Configuration of Image Processing Apparatus 100>
FIG. 2 is a block diagram illustrating a functional configuration of the image processing apparatus 100. The image processing apparatus 100 includes a first acquisition unit 201, a second acquisition unit 202, a calculation unit 203, and a generation unit 204.

The first acquisition unit 201 acquires object data including object shape information and reflection characteristic information from the input device 109 or a database (not shown). Here, the shape information is data representing the shape of the object surface, and is mesh data in this embodiment. The mesh data is data necessary for displaying a mesh model that expresses the shape of an object by a set of plate-like elements having a plurality of sides. For example, coordinate data and normal vectors of each vertex of a triangle arranged in a three-dimensional space. The data format of the shape information may be any data format that can identify the position and shape of the object, and may be a parametric model expressed by a NURBS curved surface, for example. The reflection characteristic information is data representing the reflection characteristic of the object. The reflection characteristic information in this embodiment includes a diffuse reflection coefficient kd, an ambient light reflection coefficient ka, a specular reflection coefficient ks, and a specular reflection index n in a phon specular reflection model expressed by the following equations (1) to (5). To do.
I = I _Dr + I _Ar + I _Sr Formula (1)
_{I Dr = I Di × k d} × (N · L) ··· Equation _{(2) I Ar = I Ai} × k a ··· (3)
_{I Sr = I Si × k s} × (L · R) n ··· formula (4) R = -E + 2 (N · E) N ··· Equation (5)

Here, I is the intensity of the reflected light with respect to the incident light from the light source incident on the object and the ambient light, and I _Dr is the diffuse reflection component of I (the intensity of the diffuse reflected light). Further, I _Ar is an I ambient light component (intensity of reflected light with respect to ambient light incident on the object), I _Sr is an I specular reflection component (intensity of specular reflected light), and R is a reflection vector. I _Di is the intensity of incident light from the light source that contributes to diffuse reflection in the object, and I _Ai is the intensity of ambient light incident on the object. I _Si is the intensity of incident light from the light source that contributes to specular reflection in the object, and N, L, and E are the normal vector, light source vector, and line-of-sight vector, respectively. It should be noted that parameters of other reflection models such as a Brin-phone specular reflection model may be used as the reflection characteristic information. The acquired object data is sent to the calculation unit 203 and the generation unit 204.

  The second acquisition unit 202 acquires a rendering parameter composed of viewpoint information and light source information used for rendering an object in accordance with a user instruction via the input I / F 106. In addition, you may acquire what was previously memorize | stored in memory | storage devices, such as HDD104. The viewpoint information includes the position of the viewpoint, the viewing direction from the viewpoint, and the range (view angle) viewed from the viewpoint. The light source information is the position of the light source, the direction in which light travels from the light source (light beam direction), and the intensity of light emitted from the light source. The acquired rendering parameters are sent to the calculation unit 203 and the generation unit 204.

  The calculation unit 203 calculates a shape feature amount representing the shape feature of the object surface based on the object data and the rendering parameter. Details will be described later. The calculated shape feature amount is sent to the generation unit 204.

  The generation unit 204 includes a feature image generation unit 205, a base image generation unit 206, and a synthesis unit 207. The generation unit 204 generates and outputs an output image representing an object whose gloss is enhanced according to the shape feature amount. As one of the factors that give the texture of the object, there is a fluctuation in reflection intensity based on the spatial distribution in the normal direction of the reflecting surface. In the present embodiment, the specular reflection model of Phong, which is a widely used reflection model, is assumed, and the texture of the object is enhanced by enhancing the specular reflection component (gloss) whose change in the normal direction greatly contributes to the intensity. An output image in which is emphasized is generated. Moreover, the fluctuation range of the intensity of reflected light becomes smaller at a flat surface portion than a curved surface portion with unevenness where the angle between the light incident direction and the line-of-sight direction between the neighboring meshes between the neighboring meshes is gentle. Becomes difficult to understand. Therefore, in this embodiment, the degree of gloss enhancement is increased as the shape of the object is closer to a plane. FIG. 9 shows an example of reflection. An object 901 in FIG. 9A represents a flat object having fine irregularities on the surface. An object 911 in FIG. 9B represents a curved object having fine irregularities on the surface. When the object is irradiated from the light source 902, each light beam 903 is reflected at a point on the object 901. The reflected light beam 905 enters the viewpoint 904. An alternate long and short dash line 906 schematically represents specular reflection when light is incident from a light beam 903 from the light source direction on a small region including fine unevenness on the object 901. In general, specular reflection refers to reflection in one direction in which the incident angle and reflection angle of light are the same with respect to the reflecting surface. However, when considering a small area including fine irregularities on the object surface, specular reflection in the small area appears to occur in various directions according to the normal line of the fine irregularities. That is, the specular reflection direction appears to have a spread, and this spread appears as a texture. In a general metallic material, the reflected light toward the specular reflection direction when the approximate plane of a small region is used as a reflection surface is the strongest. Therefore, when the specular reflection direction and the line-of-sight direction in the approximate plane are different, the specular reflection light to be observed becomes relatively weak. A curve 908 in FIG. 9A schematically represents the intensity of the specular reflection component from each point on the object 901 toward the line of sight. In the example of FIG. 9A, since there is no reflection point on the object 901 where the specular reflection direction of the approximate plane matches the line-of-sight direction, the maximum intensity of reflected light observed at the viewpoint position becomes small. On the other hand, a curve 918 in FIG. 9B represents the intensity of the specular reflection component from each point on the curved object 911 toward the line of sight. In general, the viewpoint from which a specular reflection light on a certain surface is obtained and the position condition of the light source are limited to a narrow range based on the normal direction of the surface. For this reason, an object close to a plane whose normal direction is a fixed direction is less likely to obtain a strong specular reflection than a curved object whose normal direction is in various directions, and the texture is difficult to understand.

  Hereinafter, each part which comprises the production | generation part 204 is demonstrated. Details of processing in each unit will be described later.

  The feature image generation unit 205 obtains the specular reflection component in the object of the incident light from the light source, and performs feature enhancement processing according to the shape feature amount to generate feature image data. The generated feature image data is sent to the synthesis unit 207.

  The base image generation unit 206 determines the diffuse reflection component of the incident light object from the light source and the intensity of the reflected light of the ambient light object, and generates base image data. The generated base image data is sent to the synthesis unit 207.

  The synthesizer 207 synthesizes the feature image data and the base image data to generate output image data.

<Processing Performed by Image Processing Apparatus 100>
FIG. 3 is a flowchart illustrating an operation procedure of a series of processes in the image processing apparatus 100. This series of processing is realized by reading a computer-executable program describing the following procedure from the ROM 102 or the HDD 104 onto the RAM 103 and then executing the program by the CPU 101. Hereinafter, each step (process) is represented by adding S before the reference numeral.

  In S301, the first acquisition unit 201 acquires object data. The second acquisition unit 202 acquires a rendering parameter. In S302, the calculation unit 203 calculates a shape feature amount based on the object data and the rendering parameter acquired in S301. In the present embodiment, the surface constituting the outline of the object is obtained based on the normal of the object surface, and the degree of variation (variance) in the normal direction within each surface is calculated as the shape feature amount. Here, the surface that constitutes the outline of an object is a group of adjacent neighbors whose normal vectors are similar when the object is viewed globally (that is, when the fine irregularities on the surface are ignored). A set of meshes. Details of the process for calculating the shape feature amount will be described below.

  First, based on the object data and the rendering parameters, a normal image in which the normal vector is recorded as a pixel value for a mesh included in the object and included in the rendering angle of view is generated. In the present embodiment, the vertex coordinates (x, y, z) of the mesh in the three-dimensional space are converted into the pixel position (i, j) in the two-dimensional image by using the general projection conversion equation (6). Convert to The normal vector (nx, ny, nz) corresponding to this vertex is recorded as the pixel value N (i, j) of the pixel (i, j).

Here, M _s , M _p , and M _v are a screen transformation matrix, a projection transformation matrix, and a view transformation matrix that are determined from rendering parameters, respectively. For the pixels corresponding to the inside of the mesh, a value interpolated from the normal vector corresponding to each vertex constituting the mesh is stored. The generation of the normal image described above (a two-dimensional image in which the pixel value N (i, j) is recorded in each pixel) can be generated by using a well-known rendering process in computer graphics. Is omitted.

  Next, a smoothing process is performed on the generated normal image to generate a smoothing normal image from which fluctuations in the normal due to fine unevenness are removed, and region division is performed on the smoothed normal image. A known Gaussian filter is used for smoothing. Let N ′ (i, j) be the pixel value of the smoothed normal image. For smoothing, a moving average filter, a median filter, or the like may be used. In addition, a known region growth method is used for region division. Note that other known methods such as threshold processing based on a histogram may be used. Each area obtained by area division is an area in which the normal vector is oriented in a substantially similar direction, and thus can be regarded as a surface constituting the outline of the object.

  Next, for each pixel (i, j) of the smoothed normal line image, a shape feature amount F (i, j) is calculated according to Expression (7) and Expression (8).

Here, R _k is a region including the pixel (i, j) in the region obtained by the region division, and num (R _k ) is the number of pixels in the region R _k . Θ (i, j) represents an angle formed by the smoothed normal vector N ′ (i, j) and a predetermined reference vector N ₀ (for example, (1, 0, 0)). The shape feature value F (i, j) in Expression (7) corresponds to the variance of the direction of the smoothed normal vector N ′ (i, j) in the region R _k including the pixel (i, j). The value approaches zero as the surface of the object corresponding to the region to which the pixel (i, j) belongs is closer to the plane. FIG. 5B shows a normal image obtained by dividing the area of the object shown in FIG. 5A, and FIG. 5C shows the shape feature value as brightness. In the example of this figure, a rectangular parallelepiped 501 having a flat surface has a small shape feature, and a sphere 502 having a curved surface has a large shape feature. With the above processing, the shape feature amount F (i, j) can be calculated for each pixel of the normal image.

  In S303, the generation unit 204 generates an output image using the object data and rendering parameters acquired in S301 and the shape feature amount calculated in S302. In the present embodiment, the specular reflection component of the reflected light is regarded as a characteristic reflection component in the texture of the object, and an output image in which the specular reflection component is emphasized as the part of the object is closer to a plane is generated. FIG. 4 is a flowchart showing details of the process (S303) for generating an output image.

In S401, the feature image generation unit 205 gives each pixel (i, j) of the normal image by giving the normal vector N (i, j) before smoothing to Expression (4) and Expression (5). The corresponding specular reflection component I _Sr (i, j) is calculated. Further, the specular reflection component corresponding to each pixel (i, j) of the normal image is enhanced according to the equations (9) to (11) using the shape feature amount F (i, j) calculated in S302.
I ′ _Sr (i, j) = I _Sr (i, j) × F _Emphasize (i, j) (9)
F _Emphasize (i, j) = α × F _Flat (i, j) +1 (10)
F _Flat (i, j) = 1 / (1 + F (i, j)) (11)

Here, F _Emphasize (i, j) in Expression (10) is an enhancement degree for the pixel (i, j), and F _Flat (i, j) in Expression (11) is a plane at the pixel (i, j). Degree. Α (> 0) is a parameter that defines an upper limit of the height of the enhancement degree, and may be acquired by a user instruction via the input I / F 106 or may be a predetermined constant. The specular reflection component I ′ _Sr (i, j) obtained by the equation (9) is larger than the original specular reflection component I _Sr (i, j) as the shape feature amount is smaller (the surface shape is closer to a plane). Become. Further, in Expression (9), the specular reflection component calculated using the normal vector N before smoothing is multiplied by the degree of enhancement, so that each variation in reflection intensity based on the spatial distribution in the normal direction is emphasized. FIGS. 6A and 6B show examples of the specular reflection component before enhancement and the specular reflection component after enhancement, respectively. The specular reflection component of the rectangular parallelepiped 501 is emphasized more strongly than the sphere 502. The obtained specular reflection component I ′ _Sr (i, j) after enhancement is recorded in each pixel as the pixel value of the feature image and sent to the synthesis unit 207. In the present embodiment, by calculating the shape feature amount for each region in S302, an edge portion is obtained for a planar portion of an object (for example, a staircase-like object) having a small number of sharp edges and mostly planar. The degree of emphasis can be increased regardless of the change in the normal direction. It should be noted that the shape feature amount F (i, j) or the flatness degree or the enhancement degree is smoothed between the neighboring areas so that an unnatural image does not occur due to the abrupt change in the enhancement degree between the areas divided in S302. The specular reflection component may be emphasized. As for the smoothing process, a known filter process is used as described above.

In S402, the base image generation unit 206 calculates the _{I Dr} by equation (2), and calculates the _{I Ar} by equation (3). A normal vector N (i, j) before smoothing is used for N in Equation (2). Further, a reflection component I _DAr (i, j) other than the specular reflection component corresponding to each pixel (i, j) of the feature image generated in S401 is calculated according to the equation (12). The reflection component other than the specular reflection component is the sum of the intensity of the diffuse reflection component and the intensity of the ambient light component.
I _DAr (i, j) = I _Dr (i, j) + I _Ar (i, j) (12)

FIG. 7 shows an example of a reflection component other than the specular reflection component. The obtained reflection component I _DAr (i, j) other than the specular reflection component is recorded in each pixel as the pixel value of the base image and sent to the synthesis unit 207.

In step S403, the combining unit 207 combines the feature image generated in step S401 and the base image generated in step S402 according to the equation (13), and sets this as an output image.
I ′ (i, j) = I ′ _Sr (i, j) + I _DAr (i, j) (13)

  FIG. 8A shows an example of an image rendered without performing the enhancement processing in S401. FIG. 8B shows an example of an output image in the present embodiment. In the output image of FIG. 8B, the gloss of the rectangular parallelepiped 501 configured with a flat surface is emphasized as compared with the rendered image of FIG. 8A, and the image expressed by enhancing the texture of the object. It becomes. Output image data representing the output image obtained by the output image generation processing is output to the output device 110 via the output I / F 107. Alternatively, it is recorded in a storage device such as the HDD 104.

  According to the present embodiment described above, it is possible to emphasize the gloss of the object in consideration of the shape of the object surface, thereby easily generating an image that easily perceives the texture of the object. Become.

<Modification>
In S302, the shape feature amount is calculated for each region obtained by dividing the normal image. However, one shape feature amount may be obtained from the entire normal image (without dividing the region). Alternatively, the variation (dispersion) may be obtained directly from the normal vector on the object surface without generating a normal image and may be used as the shape feature amount. Besides the normal vector variation, the curvature of the object surface may be used as the shape feature amount.

  Further, in the generation of the feature image in S401, the example in which the specular reflection component is emphasized using Expression (9) has been described. However, a tone curve based on a gamma curve or an S-curve is set according to the shape feature amount. The specular reflection component may be enhanced using correction.

[Embodiment 2]
The normal direction of the object surface is determined by the orientation of the surface. Moreover, generally the intensity | strength of diffuse reflection light and specular reflection light is modeled by the function of the normal direction like Formula (2) and Formula (4). Therefore, the feature of the surface shape of the object also appears in the reflected light. For example, when the shape of the object is a plane, the normal direction is constant regardless of the location, and the variation in the intensity of reflected light is smaller than in the case of a complicated shape with the surface facing various directions. Therefore, in the present embodiment, the degree of variation in the intensity of the reflected light is used as the shape feature amount. The first embodiment is different from the present embodiment in the shape feature amount calculation method in S302 described above. Hereinafter, the differences from the first embodiment will be mainly described.

  First, based on the object data and rendering parameters acquired in S301, normal rendering is performed to generate a reference image. In other words, the intensity I of the reflected light of a mesh included in the object included in the rendering angle of view is calculated according to Equation (1) and recorded as the pixel value of the reference image.

  Next, in S302, the degree of variation in the intensity of the reflected light is calculated using the pixel value I (i, j) of the reference image, and this is used as the shape feature amount. In the present embodiment, the standard deviation σ of I (i, j) shown in Expression (14) is used as the degree of variation.

  Here, Img represents the entire reference image, and num (Img) is the number of pixels of the reference image.

  Finally, in S303, the degree of gloss enhancement is calculated based on the shape feature quantity σ, and an output image in which the gloss is enhanced according to this degree is generated. Specifically, the shape feature amount F (i, j) in the first embodiment is replaced with the shape feature amount σ in the present embodiment, and the same processing as in the first embodiment may be applied. At this time, the degree of enhancement obtained by Expression (10) becomes a large value when the variation in the pixel value of the reference image representing the reflected light is small.

  According to the second embodiment described above, the gloss of the object can be emphasized in consideration of the shape of the object based on the intensity of the reflected light of the object. This makes it possible to easily generate an image in which the texture of the object can be easily perceived.

  If a plurality of objects are included in the rendering angle of view, an image area corresponding to each object may be extracted, and a shape feature amount may be calculated for each area. In that case, the gloss can be enhanced to a different degree for each object.

[Other Embodiments]
The present invention supplies a program that realizes one or more functions of the above-described embodiments to a system or apparatus via a network or a storage medium, and one or more processors in a computer of the system or apparatus read and execute the program This process can be realized. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

100 Image Processing Device 201 First Acquisition Unit 202 Second Acquisition Unit 203 Calculation Unit 204 Generation Unit

Claims (11)

First acquisition means for acquiring shape information representing the shape of the object surface and reflection characteristic information representing the reflection characteristic of the object;
Second acquisition means for acquiring viewpoint information relating to a viewpoint of viewing the object and light source information relating to a light source that applies light to the object;
Based on the reflection characteristic information, the viewpoint information, the light source information, and the shape information, in the image data representing the object, the reflection of the light of the object is increased so that the degree of enhancement increases as the flatness of the shape increases. Emphasis means to emphasize strength,
Output means for outputting the image data representing the object whose reflection intensity of the light is enhanced by the enhancement means;
An image processing apparatus comprising:   The image processing apparatus according to claim 1, wherein the case where the shape has a high degree of flatness is a case where dispersion of normals on the object surface is small.   The case where the flatness degree of the shape is high is a case where dispersion of light reflection intensity of the object obtained based on the reflection characteristic information, the viewpoint information, the light source information, and the shape information is small. The image processing apparatus according to claim 1, wherein:   The image processing apparatus according to claim 1, wherein the viewpoint information includes a position of the viewpoint, a line-of-sight direction from the viewpoint, and a range viewed from the viewpoint.   The said light source information is the position of the said light source, the direction where the light from the said light source goes, and the intensity | strength of the light which the said light source emits, The Claim 1 thru | or 4 characterized by the above-mentioned. Image processing device.   The enhancement means emphasizes the light reflection intensity of the object based on the enhancement degree for enhancing the reflection intensity of the light that is proportional to the plane degree of the shape. The image processing apparatus according to any one of claims 1 to 5.   The image processing apparatus according to claim 1, wherein the enhancement unit enhances the reflection intensity of light for each region of the object. Smoothing means for smoothing the degree of enhancement between regions near the object;
The image processing apparatus according to claim 7, wherein the enhancement unit enhances the reflection intensity of light for each region of the object based on the degree of enhancement smoothed by the smoothing unit.   2. The enhancement means emphasizes the reflection intensity of light of the object by tone curve correction based on a gamma curve or S-curve set according to the flatness of the shape. Item 9. The image processing device according to any one of Items 8 to 9.   A program for causing a computer to function as each unit of the image processing apparatus according to any one of claims 1 to 9. A first acquisition step of acquiring shape information representing the shape of the object surface and reflection characteristic information representing the reflection characteristic of the object;
A second acquisition step of acquiring viewpoint information regarding a viewpoint of viewing the object and light source information regarding a light source that shines light on the object;
Based on the reflection characteristic information, the viewpoint information, the light source information, and the shape information, in the image data representing the object, the reflection of the light of the object is increased so that the degree of enhancement increases as the flatness of the shape increases. An emphasis step to emphasize intensity,
Outputting the image data representing the object in which the reflection intensity of the light is enhanced by the enhancement step;
An image processing method comprising: