Imaging device and vehicle lighting device, vehicle

Abstract

An illumination device 110 includes a plurality of light-emitting pixels that can be individually controlled to be turned on and off, and emits reference light S1 having a random intensity distribution. A photodetector 120 measures light reflected from an object OBJ. A calculation processing device 130 reconstructs an image of the object OBJ through calculation of correlation between a detected intensity b based on an output of the photodetector 120 and an intensity distribution I of the reference light S1. The plurality of light-emitting pixels are partitioned into m (m ≥ 2) regions each containing n (n ≥ 2) adjacent light-emitting pixels. By selecting one light-emitting pixel from each of the m regions without overlaps, n light-emitting pixel groups are defined. An imaging device 100 performs sensing for each of the light-emitting pixel groups.

Description

[Technical field]

[0001] The present disclosure relates to imaging devices. [Background technology]

[0002] For autonomous driving and automatic control of headlamp distribution, an object identification system is used to sense the position and type of objects around the vehicle. The object identification system includes a sensor and a processing unit that analyzes the sensor output. The sensor is selected from cameras, LiDAR (Light Detection and Ranging, Laser Imaging Detection and Ranging), millimeter wave radar, ultrasonic sonar, etc., taking into consideration the application, required accuracy, and cost.

[0003] One type of imaging device (sensor) that is known is one that utilizes the principle of ghost imaging. Ghost imaging irradiates an object with a reference light while randomly switching its intensity distribution (pattern), and measures the optical detection intensity of the reflected light for each pattern. The optical detection intensity is the integral value of the energy or intensity over a certain plane, not an intensity distribution. Then, by correlating the corresponding pattern with the optical detection intensity, a restored image of the object is reconstructed. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 6412673 [Non-patent literature]

[0005] [Non-Patent Document 1] F. Ferri, D. Magatti, LA Lugiato, and A. Gatti, "Differential gohst imaging", Phys. Rev. Lett. 104, 253603 (2010) Summary of the Invention [Problem to be solved by the invention]

[0006] The present inventors have studied the area division method described below as a comparative technique. Note that this comparative technique should not be recognized as a publicly known technique.

[0007] 1(a) and (b) are diagrams explaining the area division method. As shown in Fig. 1(a), the lighting device includes a plurality of light-emitting pixels that can be turned on and off individually. The plurality of light-emitting pixels are divided into a plurality of sections (areas) A1 to A4.

[0008] In the comparative technique, as shown in Fig. 1(b), a reference light is irradiated onto each of the sections A1 to A4 while randomly varying the intensity distribution. Then, for each of the sections A1 to A4, a restored image of the part of the object included in that section is reconstructed by correlating the output of the photodetector with the intensity distribution of the reference light.

[0009] This comparative technique can reduce the total amount of calculations compared to a non-division method in which all pixels are used for random illumination without dividing the area into sections.

[0010] The inventors conducted a verification experiment on the non-division method and the area division method. In this verification, the irradiation area is divided into four sections. FIG. 2(a) is a photograph of the target used in the verification, which shows an elephant figurine. FIG. 2(b) is a diagram showing a restored image obtained in the non-division method, and FIG. 2(c) is a diagram showing a restored image obtained in the area division method. For the verification, a ghost imaging GI algorithm and a differential ghost imaging DGI algorithm were used. The number of pixels is 64×64 pixels, and each area is composed of 32×32 pixels.

[0011] As shown in Figure 2(c), in the area division method, the pixel values ​​of the remaining sections A2 to A4 are smaller than those of the restored image of the upper left section A1, and the boundaries between the sections are clearly visible, making the image quality inferior to the non-division method.

[0012] The present disclosure has been made in light of such a situation, and one exemplary purpose of an embodiment thereof is to provide an imaging device that suppresses deterioration of image quality while reducing the amount of calculation. [Means for solving the problem]

[0013] An embodiment of the present disclosure relates to an imaging device. The imaging device includes an illumination device that includes a plurality of light-emitting pixels that can be individually controlled to be turned on and off, and irradiates a reference light having a random intensity distribution, a photodetector that measures reflected light from an object, and a processor that reconstructs an image of the object by calculating the correlation between the detection intensity based on the output of the photodetector and the intensity distribution of the reference light. The plurality of light-emitting pixels are partitioned into m (m≧2) regions each including n (n≧2) adjacent light-emitting pixels, and n light-emitting pixel groups are determined by selecting one light-emitting pixel from each of the m regions without overlapping. Then, for each light-emitting pixel group, the light-emitting pixels included therein are switched on and off to change the intensity distribution of the reference light. A restored image of the object is restored for each light-emitting pixel group. Effect of the Invention

[0014] According to the present disclosure, it is possible to suppress deterioration of image quality while reducing the amount of calculation. [Brief description of the drawings]

[0015] [Figure 1] 1(a) and (b) are diagrams for explaining the area division method. [Diagram 2] FIG. 2(a) is a photograph of the target used in the verification, FIG. 2(b) is a diagram showing a restored image obtained using the non-division method, and FIG. 2(c) is a diagram showing a restored image obtained using the area division method. [Diagram 3] FIG. 1 illustrates an imaging device according to an embodiment. [Figure 4] 4(a) and (b) are diagrams illustrating generation of a reference beam S1 according to the embodiment. [Diagram 5] 5A to 5C are diagrams illustrating pattern control of a reference beam according to an embodiment. [Figure 6] FIG. 6(a) is a diagram showing an image obtained by the raster scan method, and FIG. 6(b) is a diagram showing an image obtained by the area division method. [Figure 7] 11 is a diagram illustrating a pixel group according to Modification 1. FIG. [Figure 8] FIG. 1 is a block diagram of an object identification system. [Figure 9] FIG. 1 shows a vehicle equipped with an object identification system. [Figure 10] 1 is a block diagram showing a vehicle lamp equipped with an object detection system; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] (Overview of the embodiment) A summary of some exemplary embodiments of the present disclosure will be described. This summary is intended to provide a simplified summary of some concepts of one or more embodiments in order to provide a basic understanding of the embodiments as a prelude to the detailed description that follows, and is not intended to limit the scope of the invention or disclosure. Furthermore, this summary is not intended to be a comprehensive overview of all possible embodiments, nor does it limit essential components of the embodiments. For convenience, the term "one embodiment" may be used to refer to one embodiment (example or variant) or multiple embodiments (examples or variants) disclosed in this specification.

[0017] This summary is not an extensive overview of all possible embodiments, and is not intended to identify key or critical elements of all embodiments or to delineate the scope of some or all aspects. Its sole purpose is to present some concepts of one or more embodiments in a simplified form as a prelude to the more detailed description that is presented later.

[0018] An imaging device according to one embodiment includes an illumination device that includes a plurality of light-emitting pixels that can be individually controlled to be turned on and off, and that irradiates reference light with a random intensity distribution, a photodetector that measures reflected light from an object, and a processor that reconstructs an image of the object by calculating the correlation between the detection intensity based on the output of the photodetector and the intensity distribution of the reference light. The plurality of light-emitting pixels are partitioned into m (m≧2) regions, each of which includes n (n≧2) adjacent light-emitting pixels. By selecting one light-emitting pixel from each of the m regions without overlapping, n light-emitting pixel groups are determined. The imaging device performs sensing for each light-emitting pixel group.

[0019] According to this embodiment, since correlation calculations for reconstructing an image are performed for each luminescent pixel group, the amount of computational processing can be reduced compared to when sensing is performed using all pixels and correlation calculations are performed collectively. Furthermore, since the luminescent pixels included in each luminescent pixel group are distributed throughout the entire sensing range, the multiple light detection intensities obtained for the n luminescent pixel groups are uniformed. Therefore, the brightness of the restored images obtained for each luminescent pixel group can be uniformed, and degradation of the image quality of the restored images can be suppressed.

[0020] In one embodiment, each luminescent pixel group may include luminescent pixels at the same position (coordinates) in m regions. In this case, the process of switching between luminescent pixel groups can be simplified. In addition, when generating one image by combining n images obtained from n luminescent pixel groups, the calculation process can be simplified.

[0021] In one embodiment, each light emitting pixel group may include light emitting pixels at different positions in the m regions, whereby the light detection intensities obtained for the n light emitting pixel groups can be uniformed, which may improve image quality.

[0022] In one embodiment, the arithmetic processing device may combine n images obtained from n groups of light-emitting pixels to generate one image, thereby obtaining a restored image with the same resolution as when sensing is performed using all pixels simultaneously.

[0023] (Embodiment) The present invention will be described below based on preferred embodiments with reference to the drawings. The same or equivalent components, parts, and processes shown in each drawing are given the same reference numerals, and duplicated descriptions are omitted as appropriate. In addition, the embodiments are not intended to limit the invention, but are merely examples, and all features and combinations thereof described in the embodiments are not necessarily essential to the invention.

[0024] In this specification, "intensity distribution is random" does not mean that it is completely random, but it is sufficient that it is random to the extent that an image can be reconstructed in ghost imaging. Therefore, in this specification, "random" can include a certain degree of regularity. In addition, "random" does not require that it is completely unpredictable, but may be predictable and reproducible.

[0025] 3 is a diagram showing an imaging device 100 according to an embodiment. The imaging device 100 is a correlation function image sensor using the principle of ghost imaging, and includes an illumination device 110, a photodetector 120, and a processor 130. The imaging device 100 is also called a quantum radar camera.

[0026] The illumination device 110 is a pseudo-thermal light source that generates a reference light S1 having an intensity distribution I that can be considered substantially random, and irradiates the object OBJ with the reference light S1.

[0027] 4(a) and (b) are diagrams for explaining generation of reference light S1 according to an embodiment. As shown in FIG. 4(a), the illumination device 110 includes a plurality (k pieces) of pixels PIX. A pixel is a unit of on / off (light on / light off) control. One pixel PIX may include a plurality of sub-pixels that are collectively set to on / off. The illumination device 110 generates reference light S1 that is spatially patterned (modulated) according to a combination of on / off states of the pixels PIX.

[0028] The plurality of luminescence pixels PIX are partitioned into m (m≧2) regions each including n (n≧2) adjacent luminescence pixels.

[0029] In this example, the lighting device 110 includes k=8×8=64 luminescence pixels PIX, and two adjacent pixels PIX in each direction (n=4 pixels) form one section. The number m of regions is k / n. The total is 16.

[0030] The multiple luminescent pixels PIX are classified into n luminescent pixel groups PG1 to PGn (PG1 to PG4). Each of the luminescent pixel groups PG1 to PG4 is formed by selecting one luminescent pixel PIX from each of the m regions without overlapping. One luminescent pixel group includes m luminescent pixels PIX.

[0031] In this example, each luminescent pixel group PGi (i=1 to n) includes luminescent pixels at the same position in m regions. The positions here are relative positions (coordinates) within each region. That is, the luminescent pixel group PG1 includes the top left luminescent pixel PIX of each of the m regions, the luminescent pixel group PG2 includes the top right luminescent pixel PIX of each of the m regions, the luminescent pixel group PG3 includes the bottom left luminescent pixel PIX of each of the m regions, and the luminescent pixel group PG4 includes the bottom right luminescent pixel PIX of each of the m regions.

[0032] In this embodiment, the imaging device 100 performs sensing for each of the luminescent pixel groups PG1 to PGn.

[0033] 5 is a diagram for explaining the pattern control of the reference light according to the embodiment. For each luminescent pixel group PGi (i=1 to n), irradiation is performed max times while changing the intensity distribution. The jth intensity distribution of the i-th luminescent pixel group PGi is expressed as I i,j It is written as follows.

[0034] For the light-emitting pixel group PGi, i,1 ~I i,max The reference light having the intensity distribution I i,j In the case of the i-th light-emitting pixel group PGi, some of the m light-emitting pixels are on (lit) and some are off (unlit), and the distribution of the on pixels changes substantially randomly. The total number of irradiations, that is, the number of patterns, is n×max. The irradiation method described in FIG. 5 is called a raster scan method.

[0035] Returning to FIG. 3, the photodetector 120 measures the reflected light from the object OBJ and outputs a detection signal D. i,j is the intensity distribution I i,jis a spatial integral value of the light energy (or intensity) incident on the photodetector 120 when the object OBJ is irradiated with the reference light S1 having the above-mentioned relationship. Therefore, the photodetector 120 can be a single-pixel photodetector.

[0036] n×max intensity distribution I 1,1 ~I 1,max , I 2,1 ~I 2,max , … I n,1 ~I n,max Reference beam S1 having i,j When (i∈1 to n, j∈1 to max) is irradiated, n×max detection signals D i,j (i∈1~n, j∈1~max) is output.

[0037] The order of irradiation of the reference beam S1 is not particularly limited. For example, 1,1 ~I 1,max , I 2,1 ~I 2,max , I 3,1 ~I 3,max , I n,1 ~I n,max Alternatively, I 1,1 ~I n,1 , I 1,2 ~I n,2 , … I 1,max ~I n,max The irradiation may be performed in this order.

[0038] The illumination device 110 may include, for example, a light source 112 that generates light S0 having a uniform intensity distribution, and a patterning device 114 that can spatially modulate the intensity distribution of the light S0. The light source 112 may be a laser, a light-emitting diode, or the like. The wavelength and spectrum of the reference light S1 are not particularly limited, and may be white light having multiple or continuous spectra, or monochromatic light including a predetermined wavelength (for example, near-infrared or infrared).

[0039] A DMD (Digital Micromirror Device) or a liquid crystal device can be used as patterning device 114. In this embodiment, patterning device 114 covers the entire measurement range 600, and has the ability to irradiate the entire measurement range 600 simultaneously.

[0040] The patterning device 114 receives the intensity distribution I i,j The pattern signal PTN that specifies i,j (image data) is given. Therefore, the calculation processing device 130 calculates the current position of the irradiation section and the intensity distribution I of the reference beam S1. i,j I know.

[0041] The processing unit 130 includes a pattern generator 132 and a reconstruction processing unit 134 .

[0042] The pattern generator 132 generates the intensity distribution I i,j may be generated randomly each time, in which case the pattern generator 132 may include a pseudorandom signal generator.

[0043] Alternatively, for a plurality of light emitting pixel groups PG1 to PGn, a set I of intensity distributions of a common pattern 1 ~I max For example, a set of patterns I of one light-emitting pixel group PG1 may be used. 1,1 ~I 1,max Regarding I 1 ~I max is used as is, and the intensity distributions of the other light-emitting pixel groups PG2 to PGn are 1 ~I max may be generated by shifting it horizontally and / or vertically by a number of pixels.

[0044] The arithmetic processing device 130 can be implemented as a combination of a processor (hardware) such as a CPU (Central Processing Unit), MPU (Micro Processing Unit), or microcomputer, and a software program executed by the processor (hardware). The arithmetic processing device 130 may be a combination of multiple processors. Alternatively, the arithmetic processing device 130 may be configured only by hardware.

[0045] The reconstruction processing unit 134 calculates a plurality of detection intensities b i,1 ~b i,max and reference beam S1 i,1 ~S1 i,max Intensity distribution of I i,1 ~I i,max By taking the correlation of i Reconstruct this image G i The resolution of the illumination device 110 is 1 / n times that of the illumination device 110.

[0046] Detection strength b i,1 ~b i,max is the detection signal D i,1 ~D i,max It is based on the detection strength b i,j and detection signal D i,j The relationship may be determined taking into consideration the type and method of the photodetector 120.

[0047] A certain intensity distribution I i,j Assume that the reference light S1 is irradiated for a certain irradiation period. Also, the detection signal D i,j represents the amount of light received at a certain time (or a very short time), i.e., the instantaneous value. In this case, the detection signal D i,j is sampled multiple times, and the detection intensity b i,j The detection signal D i,jAlternatively, some of the sampled values ​​may be selected and the integral, average, or maximum value of the selected sampled values ​​may be used. The selection of multiple sampled values ​​may involve, for example, extracting values ​​from the xth to yth values ​​in the order counting from the maximum value, excluding sampled values ​​lower than an arbitrary threshold value, or extracting sampled values ​​in a range where the magnitude of signal fluctuation is small.

[0048] When a device capable of setting the exposure time, such as a camera, is used as the photodetector 120, the output D i,j The detection intensity b i,j It can be said that:

[0049] Detection signal D i,j From detection intensity b i,j The conversion to may be performed by the processor 130 or may be performed outside the processor 130.

[0050] Image G relating to the i-th (1≦i≦n) light-emitting pixel group PGi i The correlation function of equation (1) is used to restore I i,j is the jth (1≦j≦M) intensity distribution, and b i,j is the jth detection intensity value.

number

[0051] The arithmetic processing device 130 outputs a plurality of images G obtained for a plurality of light emitting pixel groups PG1 to PGn. 1 ~G n may be combined to generate a single image, with the single image having a high resolution equal to the resolution of the illumination device 110.

[0052] The above is the configuration of the imaging device 100. Next, the advantages thereof will be described.

[0053] The number of calculations in this imaging device 100 is as follows: The number of pixels in the entire measurement range is X×Y, and the number of pixels in each light-emitting pixel group in the horizontal and vertical directions is x, y, where X×Y=(x×y)×n.

[0054] Assuming that one pattern irradiation is required to restore one pixel, the number of irradiations required to restore x × y pixels, max', is max' = (x × y) Note that the actual number of irradiations may be more or less than max', but it is roughly proportional to (x × y). Therefore, the number of calculations per section is (x × y) 2 The total number of calculations O' for all n luminescent pixel groups PG1 to PGn is expressed as follows: O'=n×(x×y) 2 It becomes.

[0055] The number of calculations O in the conventional method of irradiating the entire measurement range is O = (X × Y) 2 Since the relationship X×Y=(x×y)×n holds, according to this embodiment, the number of calculations can be reduced by O′ / O=1 / n times compared to the conventional method.

[0056] For example, consider the case where X = Y = 1024. In this case, if n = 16 and the number of pixels in the light emitting pixel group PG is x = y = 256, the number of calculations can be reduced to 1 / 16.

[0057] A reduction in the number of calculations means that the calculation time can be reduced when using a processor of the same speed, or a slower (and therefore cheaper) processor can be used to complete the process in the same amount of time.

[0058] Next, further advantages of the imaging device 100 will be described. Fig. 6(a) is a diagram showing an image obtained by the raster scan method, and Fig. 6(b) is a diagram showing an image obtained by the area division method. The verification was performed under the same conditions as Figs. 2(a) and (b), and in the area division method, each area includes 32 x 32 pixels. In the raster scan method, n = 4, and each of the light emitting pixel groups PG1 to PG4 includes 32 x 32 pixels. The maximum number of irradiations for each area or light emitting pixel group is 10,000 times.

[0059] With the area division method, it is not possible to know the overall state of an object unless images of the entire area are reconstructed, as shown in Fig. 6(b).In contrast, with the raster scan method, it is possible to detect the overall state of an object at a coarse resolution with each sensing of a group of light-emitting pixels, as shown in Fig. 6(a).

[0060] Furthermore, in the area division method, the brightness of the image obtained from each area is different, so the boundaries of the areas appear in the synthesized image, degrading the image quality. This is because the brightness of the image is i Specifically, in the upper left area, only the lower part of the 32x32 pixels corresponding to the elephant's head contains an object, so the proportion of the object in the number of pixels is low. i > becomes smaller. In contrast, in the lower left or lower right area, the elephant's body and legs make up a large proportion of the 32 x 32 pixels, and the proportion of objects represented by the number of pixels is high. i > becomes larger. This is the reason why the brightness differs from area to area.

[0061] In contrast to this, in the raster scan method, the proportion of objects represented by the number of pixels is uniformed for the light emitting pixel groups PG1 to PG4. i > can be brought closer together. As a result, G 1 ~G 4 ​​​​This makes it possible to equalize the brightness of the areas, and improves image quality without generating anything like area boundaries in the synthesized image.

[0062] As shown in FIG. 4, when each pixel group PGi includes pixels at the same position, n images G 1 ~G n It also has the advantage of simplifying the calculation process required to synthesize a single image.

[0063] The embodiment is merely an example, and it will be understood by those skilled in the art that various modifications are possible in the combination of each component and each treatment process, and that such modifications are also within the scope of the present invention. Such modifications will be described below.

[0064] (Variation 1) In Fig. 4, the multiple luminescent pixel groups PG1 to PG4 include luminescent pixels at the same positions in m regions, but this is not limited to the above. Fig. 7 is a diagram illustrating a luminescent pixel group according to Modification 1. In Modification 1, the n luminescent pixel groups PG1 to PGn are configured to include luminescent pixels at different positions in m regions. In this case, it is preferable to select the distribution of the luminescent pixels included in each luminescent pixel group PGi so that it is as random as possible. This can further eliminate the bias in the presence of objects with respect to the luminescent pixel groups PG1 to PGn.

[0065] (Variation 2) The image reconstruction algorithm to which the present invention can be applied is not limited to GI, but can also be applied to sensing devices using other algorithms such as DGI.

[0066] (Variation 3) In the embodiment, the illumination device 110 is configured by a combination of the light source 112 and the patterning device 114, but this is not limited thereto. The illumination device 110 may be configured by an array of a plurality of semiconductor light sources (LEDs (light emitting diodes) and LDs (laser diodes)) arranged in a matrix, and the on / off (or brightness) of each semiconductor light source may be controlled.

[0067] (Application) Next, the use of the imaging device 100 will be described.

[0068] 8 is a block diagram of the object identification system 10. This object identification system 10 is mounted on a vehicle such as an automobile or motorcycle, and determines the type (category) of an object OBJ that exists around the vehicle.

[0069] The object identification system 10 includes an imaging device 100 and a processor 40. As described above, the imaging device 100 generates a restored image G of the object OBJ by irradiating the object OBJ with a reference light S1 and measuring the reflected light S2.

[0070] The processor 40 processes the output image G of the imaging device 100 and determines the position and type (category) of the object OBJ.

[0071] The classifier 42 of the arithmetic processing device 40 receives the image G as an input and determines the position and type of the object OBJ contained therein. The classifier 42 is implemented based on a model generated by machine learning. The algorithm of the classifier 42 is not particularly limited, but may be YOLO (You Only Look Once), SSD (Single Shot MultiBox Detector), R-CNN (Region-based Convolutional Neural Network), SPPnet (Spatial Pyramid Pooling), Faster R-CNN, DSSD (Deconvolution-SSD), Mask R-CNN, or an algorithm to be developed in the future.

[0072] The above is the configuration of the object identification system 10. By using the imaging device 100 as a sensor of the object identification system 10, the following advantages can be obtained.

[0073] First, noise resistance is significantly improved by using the imaging device 100, i.e., the quantum radar camera. For example, when driving in rain, snow, or fog, it is difficult to recognize the object OBJ with the naked eye, but by using the imaging device 100, it is possible to obtain a restored image G of the object OBJ without being affected by rain, snow, or fog.

[0074] Secondly, by performing sensing for each pixel group PG, the amount of calculations can be reduced, which makes it possible to increase the frame rate or to select an inexpensive processor as the calculation processing unit.

[0075] In the imaging device 100, the number n of luminescent pixel groups PG may be adaptively changed according to the driving environment.

[0076] 9 is a diagram showing an automobile equipped with the object identification system 10. The automobile 300 is equipped with headlights 302L and 302R. The imaging device 100 is built into at least one of the headlights 302L and 302R. The headlight 302 is located at the very front end of the vehicle body, and is the most advantageous location for installing the imaging device 100 in terms of detecting surrounding objects.

[0077] 10 is a block diagram showing a vehicle lamp 200 equipped with an object detection system 210. The vehicle lamp 200, together with a vehicle-side ECU 304, constitutes a lamp system 310. The vehicle lamp 200 includes a light source 202, a lighting circuit 204, and an optical system 206. The vehicle lamp 200 is further provided with an object detection system 210. The object detection system 210 corresponds to the above-mentioned object identification system 10, and includes an imaging device 100 and a processing device 40.

[0078] The information on the object OBJ detected by the arithmetic processing device 40 may be used for light distribution control of the vehicle lamp 200. Specifically, the lamp side ECU 208 generates an appropriate light distribution pattern based on the information on the type and position of the object OBJ generated by the arithmetic processing device 40. The lighting circuit 204 and the optical system 206 operate to obtain the light distribution pattern generated by the lamp side ECU 208.

[0079] Furthermore, information regarding the object OBJ detected by the arithmetic processing device 40 may be transmitted to the vehicle-side ECU 304. The vehicle-side ECU may perform automatic driving based on this information.

[0080] The embodiment merely illustrates one aspect of the principles and applications of the present invention, and many modifications and changes in arrangement are permitted to the embodiment without departing from the spirit of the present invention defined in the claims. [Industrial Applicability]

[0081] The present invention relates to imaging devices. [Explanation of symbols]

[0082] OBJ object 10 Object Identification System 40 Processing unit 42 Classifier 100 Imaging Device 110 Lighting equipment 112 Light source 114 Patterning Device 120 Photodetector 130 Processing Unit 132 Pattern Generator 134 Reconstruction processing unit 200 Vehicle lighting fixtures 202 Light source 204 Lighting circuit 206 Optical system 300 Automobiles 302 Headlight 310 Lighting System 304 Vehicle ECU 600 Measurement range Section 602

Claims

1. an illumination device including a plurality of light-emitting pixels that can be individually controlled to be turned on and off and that irradiates reference light having a random intensity distribution; a photodetector for measuring reflected light from an object; a processor that reconstructs an image of the object by calculating a correlation between a detection intensity based on an output of the photodetector and an intensity distribution of the reference light; Equipped with When the plurality of light-emitting pixels are partitioned into m (m≧2) regions each including n (n≧2) adjacent light-emitting pixels, n light-emitting pixel groups are defined by selecting one light-emitting pixel from each of the m regions without overlapping, An imaging device comprising: a light-emitting element configured to detect a light emitted from each of said light-emitting pixel groups;

2. The imaging device according to claim 1 , wherein the n light-emitting pixel groups each include light-emitting pixels at the same positions in the m regions.

3. The imaging device according to claim 1 , wherein the n light-emitting pixel groups include light-emitting pixels at different positions in the m regions.

4. 4. The imaging apparatus according to claim 1, wherein the arithmetic processing unit synthesizes n images obtained from the n light emitting pixel groups to generate a single image.

5. A vehicle lamp comprising the imaging device according to claim 1 .

6. A vehicle comprising an imaging device according to any one of claims 1 to 4.

Images