Abstract:
An image detection unit extracts image feature values from images of each camera. An image conversion unit computes a blend rate according to the image feature values and composites an image of a superposition area wherein a plurality of camera images overlap. An assessment is made of a correspondence of the image feature values of each image in the superposition area, and a determination is made that a solid object is present if the correlation is weak. Furthermore, a determination is made that the solid object is present in the superposition area if the image feature values in each image have locationally overlapping portions. In such a circumstance, the image is composited with the blend rate of the image with a greater image feature value set large.

Description:
TECHNICAL FIELD 
       [0001]    The present invention relates to an image processing system and an image processing method of compositing photographed images from a plurality of cameras. 
       BACKGROUND ART 
       [0002]    In order to support vehicle driving, there is utilized an image processing system that creates and displays an overhead view image around a vehicle by photographing the surrounding of the vehicle by the plurality of cameras that have been respectively installed on the front, the back and both of the left and right sides of the vehicle, performing viewpoint conversion on these photographed images and joining together the respective images. On that occasion, although regions that the adjacent cameras photograph mutually overlap on a joint thereof, conventionally, one overhead view image has been created by selecting the photographed image to be used for display in accordance with a certain standard. However, in this technique, discontinuity arises on the joint and further in a case where there are present a pedestrian and an obstacle in the vicinity of the joint, such a problem arises that it falls into an a situation that it becomes difficult to recognize them. 
         [0003]    As a countermeasure to this problem, in Patent Literature 1, there is disclosed a technique of alternately arranging pixels in accordance with a certain role in the region in which the plurality of images overlap. In addition, in Patent Literature 2, there is disclosed a technique of deciding whether the obstacle is present on a joint portion of an overhead view image to be displayed so as to change a position that the joint portion of the overhead view image locates is disclosed. In addition, in Patent Literature 3, there is disclosed a technique of, in a case where a solid object is present in an area where field images by two cameras overlap, setting a boundary line along which the field images by the two cameras in the area concerned are to be composited such that only the image by one camera is left on a composite image in regard to the image of the solid object concerned. In addition, in Patent Literature 4, there are disclosed a technique of setting the boundary line similar to the boundary line in Patent Literature 3 and a technique of, in a case where the obstacle is present in the area where the field images by the two cameras overlap, setting composition weighting of an image of the obstacle by one camera as 1 and composition weighting of the image of the obstacle by the other camera as 0, weighting 0.5 to a portion other than the obstacle in the image by each of the cameras and compositing together them. 
       CITATION LIST 
     Patent Literature 
       [0000]    
       
         Patent Literature 1: Japanese Unexamined Patent Application Publication No. 2002-354468 
         Patent Literature 2: Japanese Unexamined Patent Application Publication No. 2007-41791 
         Patent Literature 3: WO2010/119734 
         Patent Literature 4: Japanese Unexamined Patent Application Publication No. 2009-289185 
       
     
       SUMMARY OF INVENTION 
     Technical Problem 
       [0008]    In the technique of Patent Literature 1, since the pixels of the images that have been photographed by the two cameras are alternately arranged, there is such a problem that the image becomes unclear and the solid object is displayed as a double image. In addition, in the technique of Patent Literature 2, there is such a problem that although the joint portion is moved, the joint, it results in joining that switching of the image of a newly created joint becomes discontinuous on an end of a photographing range. Also in the boundary line setting techniques in Patent Literature 3 and Patent Literature 4, likewise, there is such a problem that switching of the image on the boundary line portion becomes discontinuous. In addition, in the weighted composition technique in Patent Literature 4, only the technique of selecting weighting of the image of one camera in two values of 0 or 1 is disclosed in regard to the image portion of the obstacle. In this technique, if a process of separating the image of the obstacle from a background image results in failure, an extremely unnatural composite image will be generated. Therefore, there is such a problem that it is necessary to separate the image of the obstacle from the background image with extremely high precision, a demand for throughput and a demand for hardware capacity are grown and the system becomes expensive. 
         [0009]    In addition, although an alpha blending technique of making two images transmit by using a generally known alpha channel of the image is conceivable, in a case where two images are simply alpha-blended respectively at 50%, there is such a problem that the contrast is lowered and the luminance and color are thinned to make it difficult to see it. 
         [0010]    An object of the present invention is to provide an image processing system and an image processing method that are easy for a user to use by generating a more natural composite image that makes the solid object (the obstacle) easily visible. 
       Solution to Problem 
       [0011]    An image processing system of the present invention, in the image processing system that composites photographed images from a plurality of cameras to generate an overhead view image, includes an image detection unit that extracts image feature amounts from the images of the respective cameras and an image conversion unit that computes blend rates in accordance with the extracted image feature amounts and composites together the overhead view images in a superposition area in which the plurality of camera images overlap, wherein the image conversion unit assesses a correlation between the image feature amounts of the respective images in the aforementioned superposition area and performs composition by switching a blending method in accordance with the strength of the correlation. 
         [0012]    The aforementioned image conversion unit, in a case where it has been assessed that the correlation between the respective images in the aforementioned superposition area is weak, assesses whether there exists a portion in which the image feature amounts of the aforementioned respective images locationally overlap and performs composition by switching the blending method in accordance with presence/absence of the overlapping portion. Then, in a case where it has been assessed that there exists the portion in which the image feature amounts of the aforementioned respective image overlap, it sets the blend rate of the image that is larger in the aforementioned image feature amount as large. 
       Advantageous Effects of Invention 
       [0013]    According to the present invention, there can be provided the image processing system that generates the more natural composite image that makes the solid object (the obstacle) easily visible and is easy for the user to use. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0014]      FIG. 1  is a block diagram showing a configuration of an image processing system according to a first embodiment. 
           [0015]      FIG. 2  is an example of an image that the same subject has been photographed by a plurality of cameras installed in a vehicle. 
           [0016]      FIG. 3  is a diagram showing an example of area division of a photographing region and image composition in a superposition area. 
           [0017]      FIG. 4  is an operation sequence of the image composition in the superposition area. 
           [0018]      FIG. 5A  is a diagram showing a blend rate computing method in S 406  in  FIG. 4 . 
           [0019]      FIG. 5B  is a diagram showing a blend rate computing method in S 406  in  FIG. 4 . 
           [0020]      FIG. 5C  is a diagram showing a blend rate computing method in S 406  in  FIG. 4 . 
           [0021]      FIG. 5D  is a diagram showing a blend rate computing method in S 406  in  FIG. 4 . 
           [0022]      FIG. 6  is a diagram showing a blend rate setting method in S 404  in  FIG. 4 . 
           [0023]      FIG. 7  is a diagram showing another example of the blend rate setting method in S 404  in  FIG. 4 . 
           [0024]      FIG. 8  is a diagram showing an example of a composite image in a case where a solid object is not present in the superposition area. 
           [0025]      FIG. 9  is a diagram showing an example of a composite image in a case where the solid objet is present in the superposition area. 
           [0026]      FIG. 10  is a diagram showing an example of a composite image in a case where the solid object is present outside the superposition area. 
           [0027]      FIG. 11  is a diagram showing an example of a composite image in a case where a pedestrian has moved in the superposition area. 
           [0028]      FIG. 12  is a diagram explaining a method of computing the blend rate by using motion vector information. 
           [0029]      FIG. 13  is a block diagram showing a configuration of an image processing system according to a second embodiment. 
           [0030]      FIG. 14  is a diagram showing area division in a case of compositing images by utilizing vehicle information. 
           [0031]      FIG. 15  is a table that degrees of danger of respective areas divided in  FIG. 14  have been classified. 
           [0032]      FIG. 16  is an operation sequence of image composition in the superposition area utilizing the vehicle information. 
           [0033]      FIG. 17  is an overhead view image display example that the degree of danger has been reflected. 
           [0034]      FIG. 18  is a diagram explaining that luminance adjustment is performed by dividing a camera image into areas as a third embodiment. 
           [0035]      FIG. 19  is a diagram showing a method of matching gradation centroids of luminance histograms. 
           [0036]      FIG. 20  is a diagram showing a method of performing luminance adjustment of an area sandwiched between the superposition areas. 
           [0037]      FIG. 21  is a diagram showing a composition method for a surrounding portion in the superposition area. 
           [0038]      FIG. 22  is a diagram explaining a difference in feeling to luminance contrast by age. 
           [0039]      FIG. 23  is a diagram explaining amount-of-change restriction on the blend rate. 
       
    
    
     DESCRIPTION OF EMBODIMENTS 
       [0040]    In the following, embodiments of the present invention will be described by using the drawings. 
       First Embodiment 
       [0041]      FIG. 1  is a block diagram showing a configuration of an image processing system according to a first embodiment. The image processing system is configured such that an image around a vehicle is photographed by a plurality (n units) of cameras  101  loaded on the vehicle, photographed images of the respective cameras are composited together by an image processing device  100 , and an overhead view image around the vehicle is displayed by a monitor  109 . In the image processing device  100 , pieces of photographed image data from the respective cameras  101  are subjected to decode processing by a plurality of respectively corresponding decoding units  102  and are stored in a memory unit  107  via a bus  103 . 
         [0042]    An image conversion unit  105  performs composition processing on the photographed image data obtained from the respective cameras  101  and stored in the memory unit  107  to generate the overhead view image around the vehicle. That is, it performs lens distortion correction processing and perspective transformation processing on wide-angle camera images, creates overhead view images for every camera, performs trimming, composition, alpha-blending processing on these overhead view images, and performs processing of generating the overhead view image of the entire circumference of the vehicle. An image detection unit  106  performs edge extraction, outlie extraction, Gaussian processing, noise removal processing, threshold value processing and so forth on the photographed image data and performs detection processing for presence/absence of a white line drawn on the road, an obstacle, a pedestrian and so forth and the size of an area over which they are reflected. An encoding unit  108  performs encoding processing on the generated overhead view image and a CPU  104  controls operations of the abovementioned respective units. 
         [0043]    The overhead view image data output from the image processing device  100  is displayed by the monitor  109 . The monitor  109  is not limited in kind thereof and may be optional such as a CRT (Cathode Ray Tube), an LCD (Liquid Crystal Display), an LCOS (Liquid Crystal On Silicon), an OLED (Organic Light-emitting diode), a holographic optical element, a projector device and so forth. In addition, it may be installed inside or outside the vehicle and an HUD (Head-Up Display), an HMD (Head Mounted Display) and so forth may be utilized not limited to a planar monitor. 
         [0044]    The image processing device  100  is of the type that the obstacle and the pedestrian are detected by utilizing the images photographed by the plurality of cameras, the overhead view images of the respective camera images are composited together such that the obstacle and the pedestrian reflected in the image can be easily seen so as to generate the overhead view image of the entire circumference of the vehicle in this way. 
         [0045]    Although the image processing system of the present embodiment is so configured as to include the image processing device  100 , the plurality of cameras  101  and the monitor  109 , it may be configured such that one or both of the cameras  101  and the monitor  108  are connected to the outside of the system as external device(s). 
         [0046]    In addition, although in the present embodiment, description is made on generation of the overhead view image around the vehicle, as an application other than the above, it is applicable to a case of compositing together the photographed images from the plurality of cameras to create an overhead view image of a region to be monitored. 
         [0047]      FIG. 2  is an example of an image that the same subject has been photographed by the plurality of cameras installed in the vehicle. A front camera  201 , a left-side camera  202 , a rear camera  203 , a right-side camera  204  are installed in a vehicle  200 , and a situation that a pedestrian  205  has been walking toward the diagonally forward left side of the vehicle  200  is shown.  206  is an image that this situation has been photographed by the front camera  201  and  207  is an image that it has been photographed by the left-side camera  202 . In the present example, the respective cameras direct diagonally downward and parts  205   a ,  205   b  of the legs of the pedestrian  205  are reflected in the images  206 ,  207 . 
         [0048]    Since shooting angles are different, the leg  205   a  that has extended in a direction of an arrow extending from the front camera  201  is photographed in the image  206  photographed by the front camera  201 . On the other hand, the leg  205   b  that has extended in a direction of an arrow extending from the left-side camera  202  is photographed in the image photographed by the left-side camera  202 . That is, although they photograph the pedestrian  205  who is the same subject, the legs  205   a ,  205   b  oriented in different directions are photographed depending on a difference in photographing position between the cameras. This is a phenomenon that occurs because the pedestrian  205  who is the subject is a solid object. In a case where the subject is not the solid object and is a planar pattern drawn on the road, it is photographed in the images  206  and  207  in the same pattern and they will overlap each other if positions thereof are aligned with each other. That is, in a case where objects that extend in different directions are detected in two images when the same subject is being photographed from different directions, it can be assessed that the solid object is present. In the present embodiment, blending processing has been performed such that the overlapping portion of the plurality of camera images can be more easily seen by utilizing this feature. 
         [0049]      FIG. 3  is a diagram showing an example of area division of a photographing region and image composition of the superposition area. The surrounding of the vehicle  200  is divided into eight areas  300  to  307 . The areas photographed by the camera  201  are  300 ,  301 ,  302  and the areas photographed by the camera  202  are  300 ,  303 ,  305 . Other areas are determined relative to the cameras  203 ,  204  similarly. 
         [0050]    First, correction processing for lens distortion which would occur on an image end and perspective transformation for changing a rate of magnification according to a depth distance are performed on the photographed images. Thereby, an overhead view image that ranges the respective areas  300 ,  301 ,  302  in  FIG. 3  is created from, for example, the image  206  in  FIG. 2 . Likewise, an overhead view image that ranges the respective areas  300 ,  303 ,  305  in  FIG. 3  is created from the image  207  in  FIG. 2 . 
         [0051]    In this case, the area  300  is an area that the images of the camera  202  and the camera  202  overlap each other and hereinafter will be called a “superposition area”. The other areas  302 ,  305 ,  307  are also superposition areas that two camera images overlap each other. If the ground is flat with no projection (a solid object), the images in the same area are the same as each other and will overlap each other. That is, the superposition area means an area that the same position on the ground is photographed when the overhead view image has been created from the plurality of camera images. 
         [0052]    In a case where the image in the superposition is to be displayed, a method of displaying it by selecting one of the two images and a method of displaying it by blending and compositing together both of them are possible. On that occasion, when in a case where the solid object is present in the superposition area, if only one image is selected and displayed, it is feared that the image may be cut off in the vicinity of the joint of the composite image and a not-reflected portion (image missing) may be generated. Accordingly, in a case where the solid object (the pedestrian) is present in the superposition area  300 , display has been made by performing blending processing on the legs  205   a ,  205   b  of the pedestrian who is the solid object as shown in  FIG. 3 . Thereby, partial missing of the image of the solid object can be avoided. 
         [0053]      FIG. 4  is an operation sequence of image composition in the superposition area. As an example, a case of compositing together the images in the superposition area  300  of a camera  1  ( 201 ) and a camera  2  ( 202 ) is assumed. 
         [0054]    In S 401 , a feature amount of the photographed image in the superposition area in a camera  1  image is extracted by the image detection unit  106  to detect an object that is present there. On that occasion, the image feature amount is extracted by outline extraction by a portion with many edges and so forth and a Laplacian filter, a Sobel filter and so forth, banalization processing, color information, histogram information and various pattern recognition processing and so forth. Then, an image feature amount Q 1  such as the position of the pixel from which the edge and the outline could be extracted and the magnitude of the luminance of that edge is stored in the memory unit  107 . As the feature amount, a feature amount of the image by SIFT (Scale-Invariant Feature Transform), HOG (Histograms of Oriented Gradients) and so forth may also be utilized. In addition, the HOG feature amount and the feature amount of the shape of the pedestrian may be combined together so as to sort whether feature information that could be extracted is on the pedestrian or a substance. Then, information that is easier to use can be afforded to the user (a driver) by switching contrast enhancement processing and a way of displaying the degree of danger and so forth depending on whether it is the pedestrian or the substance. 
         [0055]    In S 402 , likewise, the object that is present there is detected from the feature amount of the photographed image in the superposition area in the camera  2  image and an image feature amount Q 2  that has been extracted is stored in the memory unit  107 . 
         [0056]    In S 403 , strength of correlations between the positions of pixels and between the feature amounts Q 1 , Q 2  extracted in S 401 , S 402  is assessed. That is, whether the pixel positions of the detected object align with each other or are gathered within a certain range and whether a difference between the feature amounts is within a certain range are assessed by computation. This is, correlations in special distance relation and semantic distance relation are assessed by performing statistical processing and clustering processing. 
         [0057]    In a case where it has been assessed that the correlation is strong (Yes) in S 403 , it is decided that the solid object is not present and it proceeds to S 404 . In S 404 , the images of the camera  1  and the camera  2  are composited together at a certain fixed blend rate. In this case, although it is also possible to select and utilize the image of either the camera  1  or the camera  2 , if the solid object has been present in the vicinity of the joint, it would be feared that the image thereof may be missed. Thus, adoption of a blending system is preferable. The overhead view image composited in S 404  is output to the monitor  109  in S 410 . 
         [0058]    In a case where it has been assessed that the correlation is weak (No) in S 403 , it proceeds to S 405  regarding that there is the possibility that the solid object may be present in the superposition area. In S 405 , whether there exist locationally overlapping portions in the image feature amounts Q 1 , Q 2  of the camera  1  and the camera  2  is assessed. 
         [0059]    In a case where it has been assessed that there exist the locationally overlapping portions in the image feature amounts (Yes) in S 405 , it means that the solid object itself is present in the superposition area (described in  FIG. 9  later) and it proceeds to S 406 . In S 406 , the blend rates are computed in accordance with the values Q 1 , Q 2  of the feature amounts that can be extracted from the respective cameras. In S 407 , composition of the images in the superposition area is performed at the blend rates computed in S 406  and the overhead view image is output to the monitor  109  in S 410 . 
         [0060]    In a case where it has been assessed that there are no locationally overlapping portions in the image feature amounts (No) in S 405 , it means that the solid object is not present in the superposition area itself and the solid object that is present around it is reflected in the camera image on the side that the feature could be extracted (the object could be detected) (later described in  FIG. 10 ) and it proceeds to S 408 . In S 408 , the camera image on the side that the feature could be extracted (the object could be detected) is selected. In S 409 , the overhead view images are composited from the camera images selected in S 408  and output to the monitor  109  in S 410 . Also in this case, in order to avoid missing of the image in the vicinity of the joint due to erroneous detection, the overhead view images may be composited by performing blending processing, giving priority to the blend rate of the camera image that the feature could be extracted. 
         [0061]    In the abovementioned operation sequence, the planar pattern drawn on the road can be discriminated from the solid object by extracting the image feature amounts of the camera images photographed from different directions in the superposition area photographed by the plurality of cameras and assessing the correlation between them. In addition, in a case where the solid object is present, locational overlapping of the feature amounts is assessed and whether the solid object is present in the superposition area or present outside the superposition area can be discriminated. Then, the favorable overhead view image can be obtained by changing the blend rates when compositing the overhead view image, conforming to each state. 
         [0062]      FIG. 5A ,  FIG. 5B ,  FIG. 5C  and  FIG. 5D  are diagrams showing methods of computing the blend rates in S 406  in  FIG. 4 . The blend rates at which the respective camera images are to be composited together are computed on the basis of the featured amounts Q 1 , Q 2  of the superposition area photographed by the camera  1  and the camera  2 . The horizontal axis takes a ratio between the feature amounts of the respective camera images detected by the image detection unit  106  and the vertical axis indicates blend rates P 1 , P 2  of the respective camera images. The ratio between the feature amounts of the camera images is obtained in the following manner. First, a result of a predetermined arithmetic operation performed on the feature amount Q 1  of the camera  1  image is defined as F (Q 1 ). A result of the predetermined arithmetic operation performed on the feature amount Q 2  of the same camera  2  image is defined as F (Q 2 ). The ratio of the feature amount of the camera  1  image is computed as F (Q 1 )/(F (Q 1 )+F (Q 2 )). Likewise, the ratio of the feature amount of the camera  2  image is computed as F (Q 2 )/(F (Q 1 )+F (Q 2 )). A predetermined arithmetic operation F will be described in detail in the following description of  FIG. 5A . 
         [0063]    In the case in  FIG. 5A , a computation formula for the blend rates is plotted as a graph of a slope  1  relative to the ratio between the feature amounts. Therefore, the blend rate P 1  of the camera  1  image and the blend rate P 2  of the camera  2  image are obtained by 
         [0000]        P 1= F ( Q 1)/( F ( Q 1)+ F ( Q 2)) 
         [0000]        P 2= F ( Q 2)/( F ( Q 1)+ F ( Q 2)). 
         [0064]    Here, various arithmetic operations are possible as for the predetermined arithmetic operation F. In the example in  FIG. 5A , a case where the value of the result of arithmetic operation is increased for the image that is high in possibility of presence of the solid object will be described. For example, an arithmetic operation for counting the number of pixels having the image feature amounts that are at least a predetermined threshold value in the superposition area is performed. In this case, the size that the image of the solid object occupies in each superposition area of the camera  1  image or the camera  2  image can be set as an element that makes the blend rates variable. In addition, arithmetic operations for computing a sum total, an average, a weighted average, a centroid, a central value of the image feature amounts of pixels in the superposition area of the camera  1  image or the camera  2  image are also possible. In this case, not only the size of the image of the solid object that occupies in the superposition area but also the magnitude of the value of the feature amount can be set as the element that makes the blend rates variable. Or, it is also possible to determine the blend rates for every pixel. In this case, Q 1  itself of a target pixel may be used as F (Q 1 ) and Q 2  itself of the target pixel may be used as F (Q 2 ). In the case in  FIG. 5A , F (Q 1 ) is compared with F (Q 2 ) and the blend rate of the image that is larger in value thereof will be set large. 
         [0065]    The case in  FIG. 5B  is also an example that the result F (Q 1 ) of the predetermined arithmetic operation performed on the feature amount Q 1  of the camera  1  image and the result F (Q 2 ) of the predetermined arithmetic operation performed on the feature amount Q 2  of the camera  2  image are used to compute the blend rate P 1  of the camera  1  image and the blend rate P 2  of the camera  2  image similarly to  FIG. 5A . Although  FIG. 5B  is the one that makes the blend rate—feature amount ratio continuously change similarly to  FIG. 5A , it is the one that the slope of a change in blend rate has been made larger than that in  FIG. 5A  on a portion in which the “ratio between the feature amounts” is close to 0.5. By such a blend rate computing method, it becomes possible to emphasize the contrast of a more characteristic image (an image that is high in possibility that the solid object is present) in spite of gentle switching of the blend rate when the “ratio between the feature amounts” is changed. Thereby, there is such an effect that it becomes possible for the user to more easily recognize the image that is comparatively high in possibility that the solid object is present. 
         [0066]    In addition, also the case in  FIG. 5C  is an example that the result F (Q 1 ) of the predetermined arithmetic operation performed on the feature amount Q 1  of the camera  1  image and the result F (Q 2 ) of the predetermined arithmetic operation performed on the feature amount Q 2  of the camera  2  image are used to compute the blend rate P 1  of the camera  1  image and the blend rate P 2  of the camera  2  image similarly in  FIG. 5A .  FIG. 5C  is also the one that makes the blend rate—feature amount ratio continuously change. However, in  FIG. 5C , in a case where the “ratio between the feature amounts” has become equal to or more than a predetermined magnitude, the blend rate of the image of that camera is set to 1 and in a case where the “ratio between the feature amounts” has become equal to or less than the predetermined magnitude, the blend rate of the image of that camera is set to 0. By such a blend rate computing method, it becomes possible to further emphasize the contrast of the more characteristic image (the image that is high in possibility that the solid object is present) in spite of gentle switching of the blend rate when the “rate between the feature amounts” is changed. There is such an effect that it becomes possible for the user to more easily recognize the image that is high in possibility that the solid object is present. 
         [0067]    Incidentally, although linear graphs have been utilized in  FIG. 5B  and  FIG. 5C , more easily visible display can be made if a LOG-curve graph that has been made to conform to visual characteristics is utilized. 
         [0068]    In addition,  FIG. 5D  is a case where has been set such that the blend rate is stepwise switched when the “ratio between the feature amounts” is changed. In this case, as the number of switching steps is increased, switching of the blend rate becomes gentle. In the example in  FIG. 5D , although it is similar to a polygonal line that the straight line in  FIG. 5A  has been stepwise changed, it will be also possible to make it have characteristics of the polygonal line similar to the polygonal line in  FIG. 5B  and the polygonal line similar to the polygonal line in  FIG. 5C  if a difference is made in the amount of change in blend rate at each switching. As described above, even when a change in blend rate relative to a change in the “ratio between the feature amounts” is discontinuous as in stepwise switching of the blend rate according to a change in “ratio between the feature amounts”, it would constitute one aspect of the present invention. 
         [0069]    Incidentally, although in any of  FIG. 5A ,  FIG. 5B ,  FIG. 5C ,  FIG. 5D , a case where the value of the arithmetic operation result becomes large for the image that is high in possibility that the solid object is present has been described, it may be the arithmetic operation F that the value of the arithmetic operation result becomes smaller for an image that is higher in possibility that the solid object is present. In this case, it is enough to simply appropriately change the graphs in  FIG. 5A ,  FIG. 5B ,  FIG. 5C ,  FIG. 5D  from the ones rising to the right to the ones rising to the left and also in this case it would constitute one aspect of the present invention. 
         [0070]    Like this, in the examples in  FIG. 5A ,  FIG. 5B ,  FIG. 5C ,  FIG. 5D , unlike the technique disclosed in Patent Literature 4, also for the image of the portion of the solid object, the blend rates can take many values other than 1 and 0. Thereby, it becomes possible to more naturally composite together the portions of the solid object in accordance with the grade of possibility that the solid object is present. 
         [0071]    In addition, the blend rates are computed for the whole superposition area or in units of pixels and are used in composition processing performed for the whole superposition area or in units of pixels. Thus, in the superposition area, generation of the unnatural joined portion of the images such as the boundary line disclosed in Patent Literature 3 and Patent Literature 4 can be prevented and it becomes possible to generate the more natural composite image. 
         [0072]      FIG. 6  is a diagram showing a blend rate setting method in S 404  in  FIG. 4 . This is a technique of performing composition by setting certain fixed blend rates for every pixel for the purpose of preventing missing of the object in the vicinity of the joint due to erroneous detection by the image detection unit  106 . Therefore, it is also applicable to the process in S 409 . 
         [0073]    In  FIG. 6 , description will be made by giving the left front diagonal superposition area  300  by way of example. The superposition area  300  is divided in a fan-like fashion and the blend rate P 1  of the image of the front camera  201  and the blend rate of the blend rate P 2  of the image of the left-side camera  202  are fixedly set for each of divided areas a 1  to a 7 . For example, in the area a 1 , since it is the closest to the front camera  201  side, the blend rate of the camera  201  is set as P 1 =0.9, the blend rate of the camera  202  is set as P 2 =0.1. P 1 =0.8, P 2 =0.2 are set in the area a 2  adjacent thereto. On the contrary, in the area a 7 , since it is the closest to the left-side camera  202  side, P 1 =0.1, P 2 =0.9 are set. The blend rates are set by giving priority to the image of the camera  201  as it is closer to the camera  201  and giving priority to the image of the camera  202  as it is closer to the camera  202  in this way. Thereby, since the image from the camera that is closer to the camera is emphatically blended in each divided area, a more easily visible image can be created. Further, in each divided area, the blend rates may be adjusted in accordance with the feature amount of each camera image. 
         [0074]      FIG. 7  is a diagram showing another example of the blend rate setting method in S 404  in  FIG. 4 . Distances from a pixel position C in the superposition area  300  to the camera  201  and the camera  202  installed in the vehicle  200  are set as d 1 , d 2 . Then, the fixed blend rates are set in accordance with a ratio between the distances d 1 , d 2 . That is, at a pixel position (that is, d 1 &lt;d 2 ) located at a distance close to the camera  201 , the blend rate of the image of the camera  201  is set high. For example, the blend rate P 1  of the image of the camera  201  and the blend rate P 2  of the image of the camera  202  are given by 
         [0000]        P 1= d 2/( d 1+ d 2) 
         [0000]        P 2= d 1/( d 1+ d 2). 
         [0075]    However, since the possibility that defocusing and distortion may be increased is high at a position that is too close to the camera, it is preferable to correct the blend rates so as to give priority to a camera that is more remote in distance. That is, when an approach limit threshold value has been designated by dth (however, d 1  minimum value≦dth≦d 1  maximum value), the blend rate P 1  of the close camera  201  image is corrected to be lowered at a position where d 1 &lt;d 2  and d 1 &lt;dth are established. 
         [0076]    For example, by replacing the abovementioned set blend rates P 1 , P 2  with each other, they are given as 
         [0000]        P 1= d 1/( d 1+ d 2) 
         [0000]        P 2= d 2/( d 1+ d 2). 
         [0077]    Thereby, there is such an effect that it is displayed with defocusing and distortion that would occur at a position that is too close from the camera reduced. 
         [0078]      FIG. 8  is a diagram showing an example of a composite image when the solid object is not present in the superposition area. It is the case where the correlation between the image feature amounts of the two camera images is strong in assessment in S 403  in  FIG. 4 . In the superposition area of the camera  1  and the camera  2 , a white line  803  that is planarly drawn on the road, a parking lot or the like photographed by the camera  1  is reflected in an image  801  of the camera  1 . A white line  804  that is drawn on the road, the parking lot or the like photographed by the camera  2  is reflected in an image  802  of the camera  2 . Since the same superposition area is photographed, the same image is generated unless the solid object is present in that area. In this case, the process in S 404  is performed to composite together the images  801 ,  802  from the two cameras at the fixed blend rates or to composite the overhead view images by selecting one image. As a result, a composite image  805  in which one white line  806  has been reflected is generated. 
         [0079]      FIG. 9  is a diagram showing an example of a composite image in a case where the solid object is present in the superposition area. It is the case where the correlation between the image feature amounts of the two camera images is weak in assessment in S 403  in  FIG. 4 . In the superposition area of the camera  1  and the camera  2 , a leg  903  of a pedestrian that has been photographed by the camera  1  is reflected in an image  901  of the camera  1 . A leg  904  of the pedestrian that has been photographed by the camera  2  is reflected in an image  902  of the camera  2 . Although the same superposition area is photographed, since the pedestrian who is the solid object is present in that area, the legs  903 ,  904  of the pedestrian extend in different directions. 
         [0080]    Further, since in assessment in S 405  in  FIG. 4 , a locationally overlapping portion  908  is present in the image feature amounts of both of them, the solid object is present in the superposition area. In this case, the process in S 406  is performed to compute the blend rates of the image  901  of the camera  1  and the image  902  of the camera  2  and, in S 407 , the images are composited together at the blend rates. As a result, an image  905  that the legs  906 ,  907  of the pedestrian have been composited together in accordance with the respective blend rates is generated. 
         [0081]      FIG. 10  is a diagram showing an example of a composite image in a case where the solid object is present outside the superposition area. It is the case where the correlation between the image feature amounts of the two camera images is weak in assessment in S 403  in  FIG. 4 . In the superposition area of the camera  1  and the camera  2 , a leg  1003  of a pedestrian that has been photographed by the camera  1  is reflected in an image  1001  of the camera  1 . Although an image photographed by the camera  2  is reflected in an image  1002  of the camera  2 , nothing corresponding to the leg of the pedestrian is present. It means that although nothing is present in the superposition area, the pedestrian (the solid object) is present near the camera  1  and has been reflected in the image  1001  of the camera  1  as the object  1003 . On the other hand, since nothing is present in the vicinity of the image  1002  of the camera  2 , nothing is reflected. 
         [0082]    Further, since in assessment in S 405  in  FIG. 4 , the locationally overlapping portion is not present in the image feature amounts of both of them, it is decided that the solid object is present outside the superposition area. In this case, the process in S 408  is performed to select the image  1001  of the camera  1  that the object  1003  is reflected, in S 409 , images are composited together by giving priority to the image  1001  of the camera  1 . As a result, a composite image  1004  that a leg  1005  of the pedestrian that has been photographed by the camera  1  is present is generated. 
         [0083]      FIG. 11  is a diagram showing an example of a composite image in a case where a pedestrian has moved in the superposition area. In a case where the pedestrian is moving from the left side in a right direction on a place in a superposition area  1100  of the camera  1  and the camera  2 , composite images of the pedestrian in the superposition area  1100  are arrayed in time series. In image composition, the blend rates are set in accordance with the image feature amounts following S 406  in  FIG. 4 . 
         [0084]    At a time t 1 , although a leg  1101  of the pedestrian that has been photographed by the camera  1  and a leg  1102  of the pedestrian that has been photographed by the camera  2  are composited together, the blend rates thereof are determined in accordance with the image feature amounts (for example, areas that the legs are reflected) and they are composited at P 1 =0.8 for the camera  1  side one and P 2 =0.2 for the camera  2  side one. By setting the blend rates in this way, the side that the area of the leg of the pedestrian is reflected large, that is, the leg  1101  that has been photographed by the camera  1  is clearly displayed. 
         [0085]    At a time t 2 , the image feature amounts (the areas) of a leg  1103  that has been photographed by the camera  1  and a leg  1104  that has been photographed by the camera  2  become the same and the blend rates thereof are equal and they are composited together at P 1 =P 2 =0.5. 
         [0086]    At a time t 3 , the image feature amount of a leg  1106  that has been photographed by the camera  2  becomes slightly larger than that of a leg  1105  that has been photographed by the camera  1  and they are composited together at the blend rates of P 1 =0.3 for the camera  1  side one and P 2 =0.7 for the camera  2  side one. 
         [0087]    At a time t 4 , the image feature amount of a leg  1108  that has been photographed by the camera  2  becomes greatly larger than that of a leg  1107  that has been photographed by the camera  1  and they are composited together at the blend rates of P 1 =0.1 for the camera  1  side one and P 2 =0.9 for the camera  2  side one. As a result, the leg  1108  that has been photographed by the camera  2  that the area of the leg is reflected larger is clearly displayed. 
         [0088]    When the same object is photographed by the two cameras in this way, the image that the contrast of the image the area of which is reflected larger has been increased can be generated by setting the blend rates in accordance with the relative ratio between the image feature amounts. 
         [0089]    In the abovementioned example, since the image feature amounts become the same as each other at the time t 2 , the blend rates have been set equally as P 1 =P 2 =0.5. However, in this case, there is the possibility that the luminances of both of them may be thinned and visual confirmation may become difficult. Thus, taking a hysteresis into account, a process of preferentially displaying the image that has been high in blend rate immediately before may be performed. Specifically, in the example in  FIG. 11 , at the time t 1  that is immediately before the time t 2 , P 1  is larger in blend rate. Thus, in the process at the time t 2  that the image feature amounts are the same as each other, a process of adding or multiplying a predetermined ratio or value to/into the detected image feature amount is performed by giving priority to P 1 . Thereby, the projected image of the camera  1  may be made easily visible by setting the blend rates as, for example, P 1 =0.6, P 2 =0.4 and so forth. Incidentally, on this occasion, they may also be set as P 1 =0.4, P 2 =0.6, anticipating the movement at the next time from the previous movement. In a case where the image feature amounts of the same level have been detected in the camera  1  and the camera  2  as in this technique, a phenomenon that the both images fade out and visual confirmation thereof becomes difficult can be reduced by blending them so as to avoid a situation that the blend rates of the two projected images become equal (P 1 =P 2 =0.5) in accordance with a time-series change in feature amount. 
         [0090]      FIG. 12  is a diagram explaining a method of computing the blend rates by using motion vector information. That is, in S 401 , S 402  in  FIG. 4 , motion vector information on optical flow is utilized for detection of the image feature amounts and the blend rates in the superposition area are computed therefrom to composite images. Motion vectors of a plurality of frames are utilized as the image feature amounts and the blend rates are computed from a ratio between sum totals of the motion vectors. 
         [0091]    Specifically, a sum total ΣCam1 of motion vectors  1203  in an image  1201  of the camera  1  and a sum total ΣCam2 of motion vectors  1204  in an image  1202  of the camera  2  are computed. From them, the blend rate P 1  of the camera  1  and the blend rate P 2  of the camera  2  are computed as 
         [0000]        P 1=Σ Cam 1/(Σ Cam 1+Σ Cam 2)
 
         [0000]        P 2=Σ Cam 2/(Σ Cam 1+Σ Cam 2).
 
         [0092]    That is, the blend rate of the camera image that is larger in motion is set larger. A composite image  1205  that includes moving objects  1206 ,  1207  is generated at these blend rates. According to this technique, it becomes possible to generate the image that is made clearer and more improved in contrast for the one that is larger than others in movement in the superposition area. 
       Second Embodiment 
       [0093]      FIG. 13  is a block diagram showing a configuration of an image processing system according to a second embodiment. In the second embodiment, a vehicle information acquisition unit  1300  is added to the configuration of the first embodiment ( FIG. 1 ). The vehicle information acquisition unit  1300  acquires vehicle control information from a vehicle to which the image processing system concerned is applied via a CAN (Controller Area Network), FlexRay and so forth. The vehicle control information is information on direction of movement, angle of steering wheel and vehicle speed of the vehicle, headlights and hazard lamps, On/Off of wipers, orientations of direction indicators and so forth, and the image processing system performs image processing that takes the degree of danger into account by utilizing these pieces of vehicle information. 
         [0094]      FIG. 14  is a diagram showing area division in a case of performing image composition by utilizing the vehicle information. In particular, in a case of performing image composition in the superposition area, area division is performed in accordance with the degree of danger. Here, the superposition areas  300 ,  301 ,  302 ,  305 ,  307  are divided into four depending on the degree of danger and the superposition area  300  is divided into A 1  to A 4 , the superposition area  302  is divided into B 1  to B 4 , the superposition area  303  is divided into C 1  to C 4 , the superposition area  304  is divided into D 1  to D 4 . 
         [0095]      FIG. 15  is a table that the degrees of danger of the respective areas that have been divided in  FIG. 14  have been classified. The degrees of danger of the respective divided areas are indicated by (large), (medium), (small) using the vehicle information (the direction of movement, the orientation of the steering wheel, the speed) as parameters. In each divided area, composition and display of images are changed in accordance with the degree of danger. 
         [0096]    In classification of the degrees of danger in the present embodiment, two speed threshold values are used. A first threshold value X is larger than a second threshold value S. In a case where the speed of the vehicle is at least the first threshold value X, it is decided that it is the dangerous speed as the speed for a parking operation. In this case, it is possible to give a driver a warning more by displaying all of the areas around the vehicle as dangerous areas. In a case where the vehicle speed is smaller than the first threshold value X, classification of the degrees of danger of the respective areas is performed using  FIG. 15 . 
         [0097]    For example, in a case where the driver intends to go forward by turning the steering wheel to the left, when a speed V is larger than the second threshold value S (V&gt;S), the left front areas A 1  to A 4  are set to the degree of danger (large). On the right front side, since there is the possibility that pedestrians who are in the areas B 1 , B 3  may rush out leftward, the degree of danger (medium) is set, and since in the rear areas C 2 , D 1 , entanglement and collision may occur due to the structure of the vehicle, the degree of danger (medium) is set. Since other areas B 2 , B 4 , C 1 , D 2  are remote in distance, the degree of danger (small) is set. Classification of the degrees of danger is performed conforming to the vehicle information in this way. These are different depending on the type of each vehicle such as the body shape of the vehicle, the small turning range, the initial speed and so forth, and these are set in accordance with each vehicle. There can be provided the display method that is more easily visible for the driver by performing composition by using danger degree information on the respective areas, when it is intended to composite the overhead view images and when it is intended to make the obstacle more easily visible. 
         [0098]    As further utilization of the vehicle information, setting as follows is possible. In a case where the own vehicle is at a standstill with the hazard lamps turned On, the degrees of danger of the areas C 2 , C 4 , D 1 , D 3  and so forth are set higher on the watch for a vehicle that is approaching from behind. In a case where the driver has made the direction indicator valid, the degrees of danger of the area located in the direction of movement of the direction of the direction indicator and the area behind it are set higher. When the headlights are On, the degree of danger of the area in the direction of movement is set higher. A way of display may be changed depending on whether the lights are directed upward or downward in a state that the headlights are On. For example, when the lights are directed upward, since it is traveling in a darker place and the field of view is narrow, not only the degree of danger on the front is set higher but also the degrees of danger of the left and right areas attention of the driver to which is liable to distract are set higher. In a case where the wipers have been turned On, since there is the possibility that the field of view may be worsened, the degree of danger of the area in the direction of movement is set higher. 
         [0099]      FIG. 16  is an operation sequence of image composition in the superposition area utilizing the vehicle information. The procedure of creating the overhead view images is based on the operation sequence in  FIG. 4  and processes that have been added will be described. 
         [0100]    In S 1601 , reading of the vehicle information and the danger degree information in  FIG. 15  is performed. 
         [0101]    In S 1601 , the vehicle speed V is compared with the threshold value X. In a case where the vehicle speed is larger than the first threshold value X, it proceeds to S 1603  and all of the areas are reset to the dangerous areas (large) on the basis of the danger degree information read out from  FIG. 15 . Thereby, that all of the areas are dangerous is displayed. 
         [0102]    In S 1604 , the composited overhead view image is output in combination with a display system that corresponds to the degree of danger for every display area on the basis of the danger degree information in  FIG. 15  or the danger degree information that has been written again in S 1603 . On that occasion, since the blend rate of the area that the solid object is present is set larger than others, the possibility of presence of the solid object (the obstacle) can be discriminated by confirming the blend rates of the respective camera images in the superposition area. That is, in the superposition area that is large in degree of danger and large in blend rate, it can be decided that it is higher in danger. 
         [0103]      FIG. 17  is an overhead view image display example that the degrees of danger have been reflected. In S 1604  in  FIG. 16 , the image conversion unit  105  changes the blend rates in accordance with the feature amount of a solid object (an obstacle)  1700  detected in the superposition area  300  so as to display the obstacle by improving its contrast. Further, in regard to areas  1701 - 1704  the degrees of danger of which have been set large from the danger degree information in  FIG. 15  or the danger degree information that has been written again in S 1603 , processes of painting out the areas and coloring the edges thereof are performed. When painting out each area, the visual contrast is improved by using a color of a hue that is different from extracted color information with reference to color information in the image feature amounts extracted in S 401  and S 402  in  FIG. 4 . In addition, after a colored layer has been superposed on the camera image that is small in blend rate, if the camera image that is large in blend rate is superposed thereon, composition can be performed without lowering so much the contrast of the camera image in which the obstacle may be reflected. 
         [0104]    Further, in regard to the area that is high in danger, that is, the superposition area that is large in blend rate and also large in degree of danger, the image conversion unit  105  performs image processing of emphasizing the edge of the object and emphasizing its contrast so as to display it such that the object becomes more conspicuous and can be clearly recognized. In regard to image characteristic parts such as the edge and the outline and so forth extracted in S 401 , S 402 , the danger can be more emphasized by performing processing of painting out them with conspicuous colors or of fringing them. In addition, as another way of utilizing this danger degree information, additional information using characters may be displayed in an area that is low in degree of danger and an area for which the degree of danger is not set in  FIG. 15 . 
       Third Embodiment 
       [0105]    Even though the blend rates are adjusted in the superposition area as described in the aforementioned embodiments 1, 2, when the brightnesses of the respective cameras are greatly different from each another, there are cases where a camera image that is high in luminance is preferentially composited so as to be easily visible and the intended effect cannot be obtained. In addition, when blending processing of the images is performed in a rectangular superposition area, there are cases where a boundary portion between the rectangles becomes conspicuous as a break depending on the blend rates. Further, a difference in feeling to the luminance contrast occurs depending on the age of the driver. Thus, in an third embodiment, a technique of correcting the luminances of the plurality of cameras and methods of correcting the boundary portion between the superposition areas and adjusting the contrast are shown. 
         [0106]      FIG. 18  is a diagram explaining that luminance adjustment is performed by dividing the camera image into areas. On that occasion, the image detection unit  106  performs luminance histogram computation and gradation centroid computation as the image feature amounts, the image conversion unit  105  performs image quality adjustment processing such as gradation adjustment and so forth in accordance with a result of detection. 
         [0107]    The overhead view images of the cameras  201 ,  202 ,  203 ,  204  that have been installed in the vehicle  200  are respectively divided into three portions, are divided into partial images E 1  to E 3  for the camera  201 , partial images F 1  to F 3  for the camera  202 , partial images G 1  to G 3  for the camera  203 , and partial images H 1  to H 3  for the camera  204 . Among them, the partial image E 1  of the camera  201  and the partial image F 1  of the camera  202  correspond to a superposition area  1800 . Likewise, the partial image E 3  of the camera  201  and the partial image H 1  of the camera  204  correspond to a superposition area  1801 , the partial image F 3  of the camera  202  and the partial image G 1  of the camera  203  correspond to a superposition area  1802 , and the partial image G 3  of the camera  203  and the partial image H 3  of the camera  204  correspond to a superposition area  1803 . In addition, luminance histograms of the partial image E 1  and the partial image F 1  in the superposition area  1800  are respectively designated by  1811 ,  1812 . 
         [0108]    Here, when the same area is to be photographed by different cameras, a difference in luminance occurs in some cases. For example, when the sun is present in the right-side direction (the camera  204  side) of the vehicle  200 , the shadow of the vehicle is photographed by the opposite side camera  202  and the partial image F 2  becomes darker than other images. In addition, the images F 1  to F 3  of the camera  202  are influenced by white balance adjustment of the camera, the luminance of the image F 2  and so forth, the images F 1 , F 3  become darker than the images E 1 , G 1  of other cameras that photograph the same area. 
         [0109]    In this case, it is possible to match visual brightnesses to some extent by computing the respective luminance histograms  1811 ,  1812  of the images E 1  and F 1  that are the superposition area  1800  and by matching the gradation centroids thereof. A way of matching the gradation centroids of the luminance histograms will be described in  FIG. 19 . Although brightness adjustment of the plurality of camera images is performed in this way, there are various methods. 
         [0110]    For example, first, in regard to the four superposition areas  1800  to  1803 , the luminance histograms of the corresponding two images are computed and luminance adjustment is performed so as to match the gradation centroids thereof. Thereafter, in regard to the intermediate images E 2 , F 2 , G 2 , H 2  sandwiched between the superposition areas, luminance adjustment is performed such that the results of adjustment in the respective superposition areas are gradationally joined with one another. For example, in the intermediate image F 2 , at a position close to the area  1800 , a value close to the adjustment result of the area  1800  is set, and at a position close to the area  1802 , a value close to the adjustment result of the area  1802  is set. Thereby, smooth luminance gradation is implemented. 
         [0111]    Or, in regard to the front side image E 2  and the rear side image G 2 , luminance adjustment may be performed so as to match the gradation centroids of the luminance histograms thereof and luminance adjustment of the images in the respective superposition areas may be performed so as to conform to a result of that adjustment. Then, in regard to the intermediate images F 2 , H 2 , luminance adjustment is performed so as to gradationally join the results of adjustment of the respective superposition areas with one another. 
         [0112]    The procedure of these adjustments may be switched in accordance with the luminance histograms of the respective images. For example, in a case where a difference in luminance between the image E 2  and the image F 2  is larger than a predetermined threshold value, first, luminance adjustment of E 2  and F 2  is performed and then adjustment of other images is performed. By switching the order of adjustments in accordance with the situation in this way, it is possible to avoid the necessity for again performing the adjustment due to an increase in luminance difference between the adjacent images as a result of simply performing sequential adjustment of adjacent images. 
         [0113]    Although, in the present example, the overhead view image of each camera is divided into three, a histogram distribution of the entire image of each camera may be computed and utilized without dividing it. For example, luminance adjustment of the images E 1  to E 3 , F 1  to F 3  may be performed by computing the luminance histogram of the whole of the images E 1  to E 3  of the camera  201  and the luminance histogram of the whole of the images F 1  to F 3  of the camera  202  and matching the gradation centroids thereof. 
         [0114]    Although, in the present example, the brightness of that image is estimated by the distribution of the luminance histogram, an average luminance, maximum/minimum luminances and so forth of images may be utilized. In a case where the average luminance of images is utilized, although it is not suited for fine control, a processing load can be reduced. In addition, although the luminance adjustment has been described, it may be matching of respective averages and centroids of Y, Cb, Cr values of YCbCr signals, adjustment of respective gradation distributions of RGB signals, and adjustment and matching of gradation distributions of respective elements in an HSV color space. Also color drift among the plurality cameras can be corrected by also utilizing color information not limited to the luminance. 
         [0115]      FIG. 19  is a diagram showing a method of matching gradation centroids of luminance histograms. It means that luminance adjustment of the superposition area  1800  is performed by matching the gradation centroid of the image F 1  of the camera  202  with the gradation centroid of the image E 1  of the camera  201 , for example, in the superposition area  1800  in  FIG. 18 . It is the same also in regard to other superposition areas. 
         [0116]    On the left side of  FIG. 19 , the luminance histogram  1811  of the image E 1  and the luminance histogram  1812  of the image F 1  are shown and the gradation centroid of each of them is indicated by a mark ▴. The gradation centroids of both of them deviate from each other by a luminance difference h. A graph  1900  on the right side indicates a transformation formula of an output luminance relative to an input luminance and is solid-lined in the polygonal-line shape. A broken line is a straight line of a slope  1  and it is the case where the input and the output are equal to each other. Adjustment of the gradation centroid of the image E 1  is performed by using this transformation formula. 
         [0117]    In order to match the gradation centroid of the histogram  1812  of the image F 1  with the gradation centroid of the histogram  1811  of the image E 1 , it is enough to deviate the gradation centroid of the histogram  1812  leftward by a correction amount h. On an input/output graph, this operation is, transformation of reducing the output luminance by the correction amount h is performed on the input luminance of the gradation centroid of the histogram  1812 . Since a reduction in luminance of only one point leads to creation of an unnatural image, adjustment for continuously reducing the luminance including its surrounding is performed in the present example. Thereby, a pixel group having a luminance in the vicinity of the gradation centroid of the histogram  1812  of the image F 1  is transformed into a pixel group that is small in luminance by h and it becomes possible to match it with the gradation centroid of the histogram  1811  of the image E 1 . That is, it becomes possible to make the visual brightness of the image F 1  approximate to the brightness of the image E 1 . 
         [0118]      FIG. 20  is a diagram showing a method of performing luminance adjustment of an area sandwiched between the superposition areas. Here, the overhead view images F 1  to F 3  of the camera  202  will be described by way of example. 
         [0119]    First, in regard to the superposition area  1800 , as described in  FIG. 19 , the luminance histograms of the image E 1  and the image F 1  are computed and a difference h 1  in gradation centroid between both of them is corrected by using an input/output graph  2001 . Thereby, a luminance-adjusted image F 1 ′ is obtained. Likewise, also in regard to the superposition area  1802 , the luminance histograms of the image F 3  and the image G 1  are computed and a difference h 3  in gradation centroid between both of them is corrected by using an input/output graph  2003 . Thereby, a luminance-adjusted image F 3 ′ is obtained. In this example, a case where correction directions of the image F 1  and the image F 3  are reverse directions is shown and also the transformation formulae of the input/output graphs  2001 ,  2003  of both of them are reversed in an up-and-down direction. 
         [0120]    Next, luminance adjustment of the image F 2  sandwiched between the adjusted images F 1 ′, F 3 ′ of the two superposition areas  1800 ,  1802  is performed. A coordinate axis z is taken in a direction from the front side toward the rear side of the image F 2 . At a position of z=0 on a front end, luminance adjustment is performed on the basis of the input/output graph  2001 , at a position of z=Zmax on a rear end, luminance adjustment is performed on the basis of the input/output graph  2003 . At a midst position z, luminance adjustment is performed such that smooth gradation is established between z=0 to Zmax on the basis of an input/output graph  2002  that the input/output graphs  2001  and  2003  have been mixed together in accordance with the position z. 
         [0121]    Specifically, assuming that X 1  is the gradation centroid of the image F 1 , h 1  is a correction amount, X 3  is the gradation centroid of the image F 3 , h 3  is a correction amount, a gradation centroid Xz and an output correction amount hz at the position z are given by 
         [0000]        Xz=X 1+( X 3− X 1)× z/Z max
 
         [0000]        Hz=h 1+( h 3− h 1)× z/Z max
 
         [0000]    and thereby Luminance adjustment of the image F 2  is performed. 
         [0122]    Thereby, luminance adjustment that is natural in gradation and is free from a strange feeling becomes possible in regard to the overhead view images F 1  to F 3  of the camera  202 . The same processing is also performed on the other intermediate images E 2 , G 2 , H 2  sandwiched between the superposition areas. Thereby, luminance correction of all of the images of the four cameras is performed by continuously performing correction in regard to the areas between them, in addition to luminance correction in the superposition areas. 
         [0123]      FIG. 21  is a diagram showing a composition method on a surrounding portion in the superposition area. When blending processing of the image is performed in the rectangular superposition area, there are cases where the boundary portion between the rectangles becomes conspicuous as the break depending on the blend rate. Therefore, although composition processing is performed on a central portion of the superposition area at the aforementioned blend rates, in regard to the surrounding portion in the superposition area, composition is performed with a slope such that it is smoothly connected with the images in areas adjacent to the superposition area. Description will be made by taking up two surrounding portions  2101 ,  2102  in the superposition area  1800  in  FIG. 18  by way of example. 
         [0124]    The upper side surrounding portion  2101  in the superposition area  1800  is close in distance from the front camera  201  in  FIG. 18  and joining with the partial image E 2  is strong. Therefore, a composition proportion thereof is gradually reduced with a slope from a predetermined blend rate so as to join with the partial image E 1  of the camera  201  at a boundary position that the composition proportion is reduced to zero. 
         [0125]    On the other hand, the left side surrounding portion  2102  in the superposition are  1800  is close in distance from the side camera  202  in  FIG. 18  and joining with the partial image F 2  is strong. Therefore, the composition proportion thereof is gradually reduced with a slope from the predetermined blend rate so as to join with the partial image F 1  of the camera  202  at the boundary position that the composition proportion is reduced to zero. 
         [0126]    By performing composition in this way, the superposition area  1800  will look natural with no break on the joints with the adjacent image E 2  and the image F 2 . Incidentally, not only in a case where the images E 1  and F 1  overlap in the superposition area  1800  as in  FIG. 18  but also in a case where they partially overlap, surroundings thereof can be smoothly composited. 
         [0127]      FIG. 22  is a diagram explaining a difference in feeling to the luminance contrast depending on the age. Such an experimental result that when looking at a  FIG. 2200 , although a twenty-something person feels that the contrast between a letter “C” and its surrounding is large as shown by contrast  2201 , a seventy-something person does not feel so much the contrast between the letter “C” and its surrounding as shown by contrast  2202  is reported in the field of human engineering (Standardization of Accessible Design Technology (AIST): Non-patent Literature). The blend rates of the superposition area are determined by reflecting the age of the user (the driver) by taking this result into account. Incidentally, age information on the driver is saved in the memory unit  107 . Then, such processing that the older the age gets, the more a composition rate is raised by giving priority to the one that is larger, even if only slightly, in each image feature amount in the superposition area is performed. 
         [0128]    For example, when the driver is young, the blend rates are determined by the computation formula of the slope in  FIG. 5A . On the other hand, for an aged person, the blend rates are determined by using the computation formula that the slope has been made large as in  FIG. 5B . Thereby, when the rate of object detection has been increased to some extent, processing of steeply increasing the blend rate of that image is performed so as to raise the contrast. In addition, processing of switching the strength of the contrast emphasis processing may be performed by the image conversion unit  105  in accordance with the age. 
         [0129]    In regard to the blending processing according to the present embodiment, the image feature amounts Q 1 , Q 2  may be computed at every pixel position and the blend rates P 1 , P 2  may be computed at every pixel position. In addition, Q 1 , Q 2  may be computed in the entire superposition area and composition may be performed by utilizing P 1 , P 2  computed on the basis of them as uniform blend rates. In addition, after processing such that the contrast is expressed emphatically has been performed in regard to a result of composition, composition may be performed and contrast emphasis processing may be performed after composition. In addition, the overhead view image may be generated by utilizing digital mirrors that side-mirrors of the vehicle have been digitized as the side cameras  202 ,  204 . 
         [0130]    In blending processing in the abovementioned respective embodiments, further, restriction on a time change in blend rate will be described. 
         [0131]      FIG. 23  is a diagram explaining restriction on an amount of change in blend rate. The vertical axis is the blend rate (P 1  or P 2 ) of one of the two cameras and the horizontal axis is a time. The time on the horizontal axis is expressed in terms of a number of frame periods, setting one scale as one frame period. 
         [0132]    First, an example of the blend rate computation result described in each embodiment will be described for every frame. A dotted line in  FIG. 23  shows an example that the blend rate that has been 0.8 up to the second frame changes to 0.5 in the third frame by computation of the blend rate, returns again to 0.8 in the fifth frame and again changes to 0.5 in the sixth frame. When applying the blend rate computation method described in each embodiment for every frame as it is in this way, for example, a change in blend rate between the second frame and the third frame becomes very sharp. In addition, a change between the fifth frame and the sixth frame is also sharp and such a satiation may occur also by noise. As a result, there is the possibility that flickering of the composite image may give the user an unpleasant feeling. 
         [0133]    In order to improve this, a difference (the change amount) with a result of the next computation processing from a directly preceding result of the blend rate computation processing is restricted within a predetermined range. An example of a case where this has been applied is shown by a solid line in  FIG. 23 , and d in the drawing is a change restriction amount. In this example, the restriction amount d is set as 10% of a directly preceding blend rate. That is, a change in blend rate in one frame period is restricted within 10% of the directly preceding blend rate. For example, in a case where the blend rate that is normally computed by the computation method described in each embodiment becomes smaller than 90% of the blend rate that has been computed directly precedingly, 90% of the directly precedingly computed blend rate is set as a new blend rate computation result. Likewise, in a case where the normally computed blend rate becomes larger than 110% of the directly precedingly computed blend rate, 110% of the directly precedingly computed blend rate is set as a new blend rate computation result. Thereby, as apparent from observation of a process of change from the second frame to the ninth frame in  FIG. 23 , a gentle and natural change in blend rate can be implemented. 
         [0134]    By using this method, it becomes possible to reduce or prevent a flickering feeling of the composite image that the user feels by reducing the sharp change in blend rate. Incidentally, although in the example in  FIG. 23 , it is made that the blend rate is computed for every frame, it may be every field and may be a frequency of one time for the predetermined number of frames. 
       REFERENCE SIGNS LIST 
       [0000]    
       
           100 : image processing device 
           101 : n cameras 
           102 : decoding unit 
           103 : bus 
           104 : CPU 
           105 : image conversion unit 
           106 : image detection unit 
           107 : memory unit 
           108 : encoding unit 
           109 : monitor 
           200 : vehicle 
           201 : front camera 
           202 : left side camera 
           203 : rear camera 
           204 : right side camera 
           205 : pedestrian 
           300 ,  303 ,  305 ,  307 : superposition area 
           1300 : vehicle information acquisition unit