DE10348618A1 - Stereoscopic image master creation method e.g. for creating image from two-dimensional image data, involves creating virtual three-dimensional image structure based on assumed three-dimensional gradation of image depth - Google Patents

Abstract

The method involves creating a virtual three-dimensional image structure (307), based on an assumed three-dimensional gradation of image depth on the basis of the image information of reproduced objects which has been determined from monocular original-image data. The original-image data is adapted to the virtual three-dimensional image structure to create a virtual three-dimensional image master and a series of individual images that reproduce the virtual three-dimensional image model are obtained. An INDPENDENT CLAIM is included for a device for displaying three dimensional depth renditions.

Description

The The invention relates to a method for creating a spatial image template according to the preamble of claim 1 and a device for displaying a Room image template according to the preamble of claim 16.

Three-dimensional Objects are only displayed two-dimensionally with monocular recording devices. That's because these Objects from a single observation site and under only one Observation angle to be recorded. In such a recording method becomes the spatial Object on a film, a photovoltaic receiver, in particular a CCD array or other photosensitive surface is projected. A spatial Impression results from the imaged object only when the object of at least two different observation points or taken under at least two different viewing angles and presented to a viewer like that will that the perceived two two-dimensional monocular images separated by two eyes and be put together in its physiological perception apparatus. To the monocular frames are combined to a spatial image template, the ones using one for that appropriate imaging process to a spatial image impression Viewers lead. such Methods are also referred to as "anaglyphics".

A for a such room image template can be used on various Be present or created way. The simplest example is Here to mention the well-known stereo slide viewer, where the viewer with one eye each, taken from a different angle Picture motive considered. In a second possibility this will be under the first viewpoint generated image with a first color and that another picture shot under the second angle with a second one Color colored. Both images become with a natural perspective difference the human eyes or the viewing angle difference of the camera system corresponding offset to create a spatial image template on top of each other printed or on top of each other projected, the viewer a two-tone glasses for viewing the Image template used. In doing so, the respective other perspective component becomes through the correspondingly colored Spectacle lens filtered out. Each eye of the observer thus receives a different according to the different point of view Picture, whereby the viewer a spatial impression of the picture template arises. Such a method is advantageous when data out a stereo camera in real time and with little equipment expense transferred and should be displayed. In addition, are also simulated spatial Illustrations with such a method for generating a spatial image template shown, with the viewer a better impression more complicated spatial structures, For example, more complicated simulated molecular structures and the like can receive.

Farther can subtler mechanisms of the physiological apparatus of perception be used to generate the spatial image template. Such is for example known that two shortly after the reaction time, successively perceived images be brought together to a subjective overall impression. If you send accordingly as a combined spatial image template in quick succession two image information, each consisting of recordings, consisting of the first, and the second Viewing angles are made, they add in the perception the viewer to a subjective overall impression using a shutter glasses together.

all mentioned However, the common method is that at least one binocular Recording the spatial Picture motif must be available in advance. The is called, that at least two shots taken from different angles be present in the first place or (as for example in drawings) produced from the beginning who must. Images or films, video sequences and the like images that were produced monocularly from the beginning and therefore only monocular Therefore image information is not for a spatial representation of the object usable. An example taken with a monocular camera Photo is a two-dimensional projection without room depth. The information about the depth of the room has been irretrievably lost through monocular imaging and must by the viewer due to experience in the picture be interpreted into it. Understandably, this results but no real spatial Illustration with depth effect.

This is disadvantageous in that at a whole series of such two-dimensional monocular generated Recordings a considerable Part of the original Effect and the information of the image is lost. The viewer does she have to to think or try to explain this to other viewers, where Naturally the original one Impression of the space with no spatial To recover the mapping process of the above examples is.

It is therefore the task of a method to create spatial image templates from two-dimensional image data, in particular from image data from image sequences, video films and the like, in which a spatial image template for an imaging process with spatial depth effect is generated from a two-dimensional image.

These The object is achieved by a method according to the features of the claim 1 solved, the dependent claims contain at least ausgestaltende features of the invention.

at In the following description, under the term "archetype", the initially given monocular made two-dimensional image understood. It is immediate understand that an application of the method according to the invention described below also on sequences is applicable by such Urbildern and therefore readily for moving Images, in particular video or Filmaufnah men used can, if this from a series of successive illustrations exist or be transferred to this can.

According to the invention the basis of image information determined from monocular original image data imaged objects on a guess-based image depth gradation based virtual three-dimensional image framework generated. The original image data are applied to the virtual three-dimensional image framework for generating adapted to a virtual three-dimensional image model. The Data of the virtual three-dimensional image model are used as a template to create the spatial image template for the imaging process with spatial Depth effect used.

It become according to the invention thus first the determined on the two-dimensional image imaged objects. Then each of these objects is a guess about their Assigned room depth. The result is a virtual three-dimensional model, being the original one Image data of the two-dimensional image on this virtual three-dimensional Model adapted become. This virtual three-dimensional model now forms virtual object whose data is the starting point for generating the Represent room image template.

On The monocular master image data is used to determine the image information a method for edge detection of the imaged objects executed with a generation of an edge-marked image. there become in the presumption-based image depth gradation Urbildareale due to a determined edge richness different virtual depth levels, especially associated with a background and / or foreground.

Here the realization is used that detailed and thus edge-rich objects in general to a different image depth and thus include deep level, as low-detail and thus low-edge objects. The step of Edge detection therefore sorts out components of the original image, from which is assumed to be in the background of the picture they are located and separated from those in the foreground or one further depth level are to be assumed.

at another approach to determining the image information For example, a method for determining the color information of given original image areas is performed. there becomes at the guess-based depth of image at least a first identified color information of a first virtual Depth plane and a second color information of a second virtual Assigned depth level.

there here the fact of experience is applied that certain colors or color combinations in certain image motifs, preferably in a different depth plane occur as other colors or color combinations. examples are therefor Blue as a typical background color in landscapes on the one hand and red or green on the other hand, as typical foreground colors of the depicted subject.

The Edge detection method and method for determining the Color information can both individually or in combination with each other, especially a combined application of edge detection and detection the color information further differentiation options of the original image data, in particular a finer setting of further depth levels allowed.

On the edge-marked image is in a suitable embodiment, a soft-focus method for reinforcement and used to unify an edged original picture area. This will be possible on the one hand Error in edge detection balanced and on the other side lying, not accidental reinforced given structures. Optionally the values of the edge-marked image are additionally corrected for tone value.

On the basis of the softened and / or additionally tone-corrected edge-marked image, an assignment of a relevant image section based on the tonal value of a pixel to a depth plane is carried out. The structures of the edge-marked image, which is softened and optionally tone-corrected, are now assigned to individual defined depth levels, depending on their tone value. The edge-marked, softened and optionally tone-corrected image bil Therefore, the basis for a clear assignment of the individual image structures to the depth levels, such as the defined virtual background, a virtual image plane or a virtual foreground.

at an executed thereby Fixed point definition, the color and / or tone values are limited to a predetermined value. This becomes a virtual pivot for the later set to be generated individual views. The selected color and / or Tonwert a reference value of a virtual image plane and thus a virtual depth background of a foreground that is virtually out of the picture plane.

The Assigning a virtual depth layer can be done in several ways respectively. The process steps already described expediently an assignment of a depth level to a given color and / or brightness value of an image pixel. Objects with image pixels, which thus have the same color and / or brightness values thus assigned to a depth level.

alternative There is also the possibility of arbitrarily determined Image sections, in particular a picture edge and / or the center of the picture, assign to a virtual depth layer. This is especially a virtual "curvature", "strain", "tilt" and the like achieved three-dimensional image effects.

To the Creating the virtual three-dimensional image model becomes the virtual one three-dimensional image framework as a virtual deformed according to the virtual depth planes Net structure generated and the two-dimensional archetype in a mapping process as a texture adapted to the deformed network structure. The network structure forms doing a kind of virtual three-dimensional "matrix" or "profile shape", while the two-dimensional archetype represents a kind of "elastic cloth" that over the Matriar is stretched and pressed into the matrix in a kind of virtual "thermoforming process". The result is a virtual three-dimensional image model with the image information of the two-dimensional archetype and the additional the Original image imprinted "virtual Thermoforming structure "the virtual three-dimensional matrix.

From This three-dimensional image model can be virtual binocular or Also, multi-focal views are derived. That happens by from the virtual three-dimensional image model from a Set of virtual observation angles a series of virtual, Play the views of the virtual three-dimensional image model Frames are generated, where a fixed depth corresponding image sections of the original image corresponding to the virtual Observation angle shifted and / or distorted. The virtual Three-dimensional image model thus serves as a virtual spatial Object that is considered to be virtually binocular or multi-eyed, where doing this, virtual views are gained that are appropriate differ from the observation angles.

These virtual frames are after one for the imaging process with additional room effect suitable algorithm for generating a spatial image template combined. The virtual frames are like binocular or real treated multi-ocular captured frames, which now for a three-dimensional Preparation method suitably prepared and combined. This is a virtual binocular or multi-cellular Picture information before, for any spatial Imaging method can be used.

To the Creating the room image template is in one embodiment the process an image processing of individual image areas of the original image, in particular scaling and / or rotating and / or mirroring executed and the generated space image template by means of an overlying monofocal lens raster displayed.

there be the image structures in the virtual three-dimensional Image model assigned to certain depth levels, so changed that These are sufficient when displaying the generated space image template Accommodation stimulus for the to provide contemplating human eye. The highlighted image structures either by means of optical imaging through the lens grid perceived before and behind the given image plane and thus lead to a spatial impression when viewing the picture. This method only requires a relatively simple designed room image template in conjunction with a simple execution of the Imaging method with spatial depth effect.

The two-dimensional archetype can also be displayed directly without any image processing by the monofocal lenticular. The two-dimensional archetype image can thus be used immediately as a spatial image template for display by the monofocal lenticular grid. Such a procedure is particularly expedient if simple image structures in front of a homogeneously structured background, in particular characters in front of a uniformly formed text background, are to be displayed with depth effect. The obtained by the imaging effect of the monofocal lens raster Akkomodationsreiz for the viewing eye then effects a depth effect, wherein the original image does not have to be prepared beforehand for such a display.

A Apparatus for displaying a spatial image template is characterized by a two-dimensional Room image template and an over the spatial image template arranged monofocal lens grid characterized. The monofocal lenticular forms here areas of the spatial image template and causes a corresponding Akkomodationsreiz in observing Eye.

The Two-dimensional image template is expediently made of a mosaic from the grid structure of the lens grid associated image sections executed wherein substantially each one image section is an imaging object for essentially one associated each Lens element of the monofocal lens grid is. The two-dimensional Picture template is therefore in a totality of individual image areas divided, each by a lens element are displayed.

at This device are in principle two embodiments of the image template and in particular the image areas possible. In a first embodiment the image sections are essentially unchanged image components of two-dimensional image template of the archetype. It means that in this embodiment essentially unchanged two-dimensional image forms the spatial image template for the lenticular grid. In this embodiment thus, apart from size changes or scaling the entire image, to image editing omitted individual image areas.

at a further embodiment are the image sections to compensate for the imaging effects the lens grid scaled and / or mirrored and / or rotated. This achieves an improved image quality, although the effort for the Creation of the room image template increases.

The two-dimensional image template is in particular a on a display generated image while the lenticular grid on the surface the display is attached. The lenticular is thus on a pre-existing display, such as a tube or Flat screen, attached to a suitable place and is located thus above the displayed on the screen. This arrangement can be in a very simple way.

In a first embodiment The lenticular is a grid-like, adhering to the display surface Fresnel lens assembly executed. The use of Fresnel lenses ensures a flat and simple Design of the lenticular grid, wherein the groove structures typical for Fresnel lenses in the manner known in the art in a transparent Plastic material, in particular a plastic film are incorporated can.

In a second embodiment is the lenticular grid as a grid-like, in particular flexible, on the display surface adhesive zone plate assembly executed. A zone plate is a concentric one System of light and dark rings caused by light interference a bundling of the passing light effect and thus an imaging Enable effect. Such an embodiment is by printing a transparent flexible film in less expensive and less expensive Way to produce.

at a third embodiment For example, the lenticular grid is also conventionally shaped as an array Convex lenses possible, However, although the thickness of the entire arrangement and thus their material consumption increases.

The Method and the device will be described below with reference to exemplary embodiments be explained in more detail. To clarify serve the attached figures. It will be for same or equivalent process steps and process components the same reference numerals are used. It shows:

1 a first part of an exemplary schematic program flowchart of the method,

2 an exemplary flowchart of edge detection,

3 a second part of an exemplary schematic program flowchart of the method,

4 an exemplary selection menu for performing the edge detection,

5a an exemplary prototype,

5b an exemplary edge-marked image as a result of on the exemplary archetype 5a executed edge detection,

6a an exemplary result of one on the edge-marked image 5b executed soft focus,

6b an exemplary result of one on the edge-marked image 6a executed tonal correction,

7a an example selection menu for a fixed point definition,

7b an exemplary fixpoint-defined image,

8a a schematic example of graphical objects in a schematic two-dimensional archetype,

8b a schematic example of a depth-plane assignment of the graphical objects 8a and generating a virtual three-dimensional image model along exemplary sections along the lines AA and BB 8a .

9a a schematic example of a virtual binocular viewing and projection of the virtual three-dimensional image model along the line AA from the 8a and 8b .

9b a schematic example of an exemplary virtual binocular viewing and projection of the virtual three-dimensional image model along the line BB of the 8a and 8b .

10 a schematic example of a virtual frame formation from an exemplary viewing angle along the exemplary line AA 9a .

11a a series of exemplary virtual frames of different viewing angles using the archetype 5a .

11b an exemplary combination of in the 11a shown virtual frames in an exemplary room image template for an imaging process with additional depth effect,

12a , b exemplary representations of a two-dimensional image template and a monofocal lens raster located above it,

13a Fig. 2c shows exemplary representations of an image of a two-dimensional image section by means of the monofocal lens raster of the preceding figures.

The 1 and 3 show in two parts an exemplary schematic flowchart of the method. 2 discusses an edge detection method in a more detailed schedule. The 4 to 11b show exemplary results and further details of the process of the invention explained in the flowcharts.

The starting point of the method is a set of original image data 10 a given two-dimensional, suitably digitized, archetype. If the original image is a single image as part of an image sequence or of a film that has been digitized in the following description, it can be assumed that all further individual images of the image sequence can be processed in a manner corresponding to the individual image. Therefore, the method exemplified below is also applicable to image sequences, films, and the like.

Appropriately, it is assumed that the original image data 10 in an image file, a digital storage device or a comparable storage unit. This data can be generated by the usual means for generating digitized image data, in particular by a known scanning process, digital photography, digitized video information and the like, further known image acquisition methods. This includes, in particular, image data obtained from video or film sequences using so-called frame grabbers. In principle, all known image formats, in particular the BMP, JPEG, PNG, TGA, TIFF or EPS format, can be used as data formats in all respective versions. Although reference is made in the exemplary embodiments described below to figures that are depicted in black-and-white or gray values for reasons of representation, the original image data can easily contain color information.

The original image data 10 be in a read-in step 20 loaded into a working memory for carrying out the method. In a process step of fitting 30 First, the original image data are adapted for optimal process execution. The customization 30 The image properties include at least one of changing the image size and the color model of the image. Smaller images are usually preferred when the computational time of the method is to be minimized. However, a picture size change can also be a possible source of error for the method according to the invention. In principle, all color models currently in use, in particular RGB and CMYK or grayscale models, but also Lab, index or duplex models can be used as the color model to be adapted as required.

For further processing, the adjusted image data in one step 40 cached for repeated access. The cached image data 50 form the basis of essentially all subsequent data operations.

Depending on the assumed spatial image structure, ie the presumed gradation of the depth planes in the archetype, now optionally follows under ei Access to the cached image data 50 either a change of the color channel / the color distribution 60 or a conversion of the image data into a gray-scale graded image by means of a gray level graduation 70 , The gray value gradation 70 is especially advantageous if it can be assumed that a predominantly the object contours shown in the image is to be assigned a depth information. In this case all color information of the image is equally relevant for a deep interpretation of the original image and can therefore be converted into gray values in the same way. A modification of the color channel or of the color distribution in the image data is expedient if it is to be assumed that a color channel is essentially the carrier of the interpreted depth information and should therefore be particularly emphasized or taken into account for the following processing. In the exemplary description of the method sequence given here, it is also assumed for reasons of better illustration, in particular with regard to the figures, that the buffered image data 50 regardless of their color values are converted into gray values, the color information remains unchanged.

In the further course of the process, an edge detection closes 80 at. The assumption here is that the depth levels interpreted into the two-dimensional archetype are primarily defined by the objects present in the image motif. For example, it can be assumed that richly textured objects, which are thus heavily influenced by contours and thus edge-like structures, are present predominantly in the foreground of the image, and low-contour, washed-out and thus low-edge objects form the image background. The edge detection method 80 is executed in order to uniquely identify the different areas of the archetype, which belong to different depth levels due to their structuring, and to distinguish them from each other as clearly as possible.

2 illustrates a schematic and exemplary flowchart for edge detection. 4 shows in conjunction with this an exemplary input menu 89 determining the changes to be made to the brightness values of a central pixel and a specified pixel environment. The image pixels defined by their gray value 81 are processed continuously in a loop process. First, a selection is made 82 of a pixel and reading in its brightness value 83 , This brightness value is multiplied by the largest possible positive value (in the example shown here with the arbitrary value +10), resulting in a very bright image pixel 85 is produced. On the other hand, a brightness value of a respective pixel lying to the right thereof is given a value which is as negative as possible (in the example shown here with -10) in one step 86 multiplied, creating a very darker pixel 87 is produced. Then in one step 88 read in the next pixel. The result of edge detection is an edge-marked image. Where the original image shows a large structural and thus edge richness, the edge-marked image data now given consist of a structure of very light or very dark pixels, while low-structured and therefore contour-poor and edge-poor image areas have a uniform dark color. The structure of the alternately very light and very dark pixels and the object marked thereby has a higher average brightness value than an area of consistently darker pixels.

Adjacent structures will hereinafter be referred to as a "softening" process step 90 strengthened. In this case, the brightness values of a specific selected pixel quantity in the edge-marked image are averaged according to a specific algorithm and assigned to the pixels of the selected quantity. In particular, a Gaussian blur has proven its worth here. In the soft-edged edge-marked image, the object structures stand out as a lighter amount of pixels from the rest of the image part and allow identification of a uniform object.

Optionally, then in one step 100 tonal correction of the edge-marked blurred image. In this case, the tonal values of the pixels are preferably corrected in such a way that the most distinct contrast between the object structure and the rest defined as the background of the image results.

The next step in the process is a fixed point fix 110 designated. In this step, the color and / or gray values of the edge-marked blurred image are limited to a certain value so as to de facto define the virtual fulcrum of the virtual single views to be generated. The fixed point fixing 110 in other words, defines the objects or structures that are supposed to be virtually located in front of or behind the image surface and later displayed in their depth effect.

Furthermore, optional in one process step 120 other fixed point options are taken into account. For example, a first assumption can be made that larger blue areas predominantly form a background (blue sky, water, etc.), while smaller, sharply defined and colorfully prominent objects form the foreground of the image. Similarly, certain color values may be assigned certain virtual depth levels from the beginning. So can For example, color values corresponding to a face color are assigned to a virtual depth plane corresponding to an average image depth. Likewise, defined image sections, such as the image border or the image center certain depth levels, for example, the foreground or the background can be assigned, with a "bias" or "curvature" of the later generated spatial image can be generated.

The gradations of the virtual depth planes produced in this way create a virtual three-dimensional image framework that serves as a distortion mask or "displacement map" and can be visualized in the form of a gray scale mask.This virtual three-dimensional image framework becomes in one step 130 saved for further use.

The virtual three-dimensional image framework serves as a distortion mask and virtual shape for creating a virtual three-dimensional image model. It is in a process step 150 who in 3 is called "Displace", placed the original image as a texture on the virtual image framework and distorted so that the corresponding pre-image sections on the virtual depth levels "deep drawn" ie assigned to these depth levels. From this virtual three-dimensional image model, individual virtual images are now transformed from a number of different virtual viewing angles 160 of the virtual three-dimensional image model generated by a virtual projection of the image data of the virtual three-dimensional image model according to known perspective mapping laws.

In a combination step 170 For example, the virtual frames are combined according to an algorithm set for the additional depth effect imaging method such that finally image data 180 for the three-dimensional mapping of the initial archetype.

In the following, some image processing will be explained in more detail by means of examples. 5a indicates a generally colored, two-dimensional archetype 200 , As can be seen from the picture, a number of plants are obviously in the foreground of the image, while obviously located in the background located indistinct port facilities, buildings and a largely unstructured beach. Furthermore, the background, which is practically at infinity, is in the archetype 200 formed by a softly running sky. Again 5a It can be seen that the plants arranged in the obvious foreground are characterized by a considerable amount of detail compared to the background, which is manifested inter alia in a large number of "edges", for example in the area of the leaves or the flowers It is therefore obvious, the density of the edges in the archetype 200 as an indicator of the spatial position of the objects presented.

5b shows one from the archetype 200 edge-marked image obtained after grayscale conversion and optional size correction 210 , There, where the structurally rich plants from the in 5a shown archetype 200 show the edge-marked image 210 a multiplicity of bright-pixel-marked edges, which lead to a higher average image brightness, especially in the right-hand image area. In contrast, both the sky and the beach area from the archetype 200 low edge and therefore in the edge-marked image 210 mostly dark, while those in the archetype 200 recognizable building produce a few edge structures in the form of isolated bright pixels.

The 6a and 6b show a softened edge-marked image 220 and a soft-edged edge-marked and additionally tone-corrected image 230 , On the softened picture 220 It can be seen that the right image part differs from the left image part by a higher image brightness value. This difference is even more evident in the tone-corrected image 230 in 6b , The richness of edges in the area of the plants of the archetype, in other words the structure richness of the assumed foreground, is shown in the pictures 220 and 230 clearly as a bright area. It is clear in the tone-corrected image 230 on the left half of the picture a slightly lighter stripe can be seen, which is, however, much darker than the image area of the plants. This strip corresponds to the depicted buildings from the archetype 200 out 5a , The much darker brightness value refers to the lower-edge structure of the buildings depicted and thus to their arrangement in the assumed background image.

In the softened and tone-corrected image, the sky and the beach form the archetype 200 a uniformly dark surface. Although the beach is more likely to be the middle foreground of the picture than the background formed by the sky, the central edge position of the edge-marked, softened and tone-corrected image alone can not be clearly determined. Here, an assignment of the beach to a virtual middle depth level is appropriate due to the yellow or brown color value, which in this example clearly differs from the color value of the blue sky.

This is with the above-mentioned fixed point specification 110 possible. 7a shows a related example menu 239 . 7b the the menu corresponding image 240 , In a histogram 241 are a series of color channels shown in the in 7a embodiment shown are a series of gray levels. The corresponding gray values are in a gray scale bar 242 displayed. In the left part of the histogram 241 , or the gray scale bar 242 are the dark brightness values, in the right part are the bright brightness values. The size of the histogram bars indicates the frequency distribution of the corresponding gray values. It can be seen that the bright area of the softened, or tone-corrected image 220 or 230 in a broad maximum of the histogram 241 shows while the dark areas in the pictures 220 and 230 to a maximum in the left part of the histogram 241 at the dark brightness values leads. Using indicator pointers 243 certain brightness values can be selected. Using the buttons 245 can brightness values of selected pixels directly from the image 241 into the histogram 241 be read out and transmitted.

In the example shown here turns out that the beach from the archetype 200 corresponding area in its brightness value from the sky from the archetype 210 corresponding image section distinguishes. This can be done by means of a selection indicator 244 be selected as a virtual image plane and forms a possible fixed point for virtual single views of the later to be generated virtual three-dimensional image model.

The 8a and 8b show in a very highly schematic example a depth-plane assignment and a construction of a virtual three-dimensional image frame. In 8a is a highly schematic monocular two-dimensional archetype 301 represented, the individual objects were already identified in their spatial position in the image by the previously described contour recognition method. This in 8a exemplified schematic prototype 301 has a first object 303 , a second object 304 and a third object 305 on, in front of a surface identified as background 306 are arranged and stand out from this.

The above-described methods for contour marking, for fixed-point definition and further assumptions about the image depth allow it, for example, for the schematic archetype 301 in 8a make sense, the first object 303 in the foreground, while the objects 304 and 305 continue to be assigned in the image background suspected depth levels. The area 306 forms an image background that is virtually at infinity. In 8b that's from the mappings of the objects 8a generated virtual image framework to the corresponding depth levels 307 in a section along the lines A - A and the line B - B aus 8a shown. The sections along the section lines A - A and B - B thus provide a virtual "height profile" of the virtual image framework 8b it can be seen, is the object 303 arranged in this virtual "height profile" at the top depth level, while the object 304 is assigned to an underlying depth level. The object 305 forms another depth plane in the virtual frame in the 8b out. The virtual depth layer of the image background 306 is in 8b for reasons of representation, relatively close to the depth planes of the other objects 303 . 304 and 305 arranged. An expedient virtual image framework must expediently have depth-plane graduations which correspond to the assumed actual spatial position of the objects. Thus, the virtual depth plane of the image background should therefore expediently be arranged such that their distance from the other defined depth planes of the virtual image framework corresponds to a multiple of the distances between the respective others. For example, become the distances between the virtual depth planes of the objects 303 and 304 or between the virtual depth plane of the object 304 and 305 defined in the range of a few meters, the appropriate virtual distance between the depth plane of the object 305 and the deep level of the background 306 for a realistic scaffold expediently assume a size that is in the kilometer range, as experience has shown that objects in the background, that they are displayed virtually unchanged with small differences in the viewing angle.

The two-dimensional archetype is adapted to the virtual framework. In the in the 8a and 8b shown schematic example, this is done so that the image data of the original image 301 , in particular the image information of the individual pixels, are virtually assigned to the individual depth levels in the virtual image framework. The result is a virtual three-dimensional image model, which in the example shown here is comparable to an arrangement of "scenes" in which the object 303 is virtually at the height of a first virtual depth plane in the foreground and the other located on the levels of the corresponding other depth levels "scenes" of the objects 304 and 305 "Concealed".

In addition to this, fluid transitions between the individual virtual depth levels can be achieved by refining the grid of the gradations of the virtual distances between the individual depth levels and by further grading the individual depth levels. On the other hand, it is also possible to use the edges of the depth planes or the objects located on the depth planes to deform virtually so that they merge into each other. For example, it would be the schematic object 303 in 8a possible to virtually deform the edge of its depth plane so that the object 303 gets a virtual spherical curvature. In a corresponding manner, the depth planes of the virtual image framework can be deformed so that the image information of the two-dimensional archetypal image imaged in the context of a suitable or desired virtual three-dimensional image model can in principle have any shapes or distortions which either largely correspond to a real three-dimensional body shape or else can be enriched with any artistic effects.

The 9a and 9b show one from the virtual framework from the 8b generated virtual three-dimensional image model 807 in section along the lines A - A and B - B aus 8a and their virtual images from two viewing angles 351 and 352 , The in the 9a and 9b illustrated configuration corresponds to a binocular viewing of a three-dimensional object that is performed virtually within the method. According to the laws of perspective, the virtual three-dimensional objects appear 303 . 304 . 305 and 306 from the respective virtual viewing angles 351 and 352 from different shifted against each other. This perspective shift is the basis of the binocular or multi-eyed viewing of spatial objects and is virtually modeled in the context of the method according to the invention.

10 shows an example of a virtual generated shift under the influence of the virtual viewing projection from the virtual viewing angle 352 using the example of the section of the virtual three-dimensional image model 9a , For calculating the virtual perspective displacement of the virtual objects of the virtual three-dimensional image model, different methods can be employed. At the in 10 By way of example, the principle of centric stretching is applied, the virtual being from the viewing angle 352 from targeted objects 303 . 304 and 306 on a virtual projection plane 308 be projected and thereby experience a change in size. The projection plane can be located virtually in front of the virtual three-dimensional image model as well as behind the three-dimensional image model. A location of the virtual projection plane within the virtual three-dimensional image model, for example in one of the screen levels defined in the fixed point determination, is also possible and even most convenient since such projection best reflects binocular viewing conditions. At the in 10 The projection shown forms the viewing angle 352 at the same time a projection center, wherein the virtual three-dimensional image model is considered, as it were, in a virtual "incident light method" in which the radiation source virtually coincides with the camera.

Other Virtual projection techniques are also applicable. So can the projection center virtually behind the background of the be arranged in a virtual three-dimensional image model and the corresponding objects of the virtual depth planes as a "silhouette" on a suitably positioned Projection plane projecting from a viewing angle is looked at. In such a virtual projection appear the objects located in the virtual foreground opposite the magnified virtually behind them objects, causing an additional space effect can be caused.

Farther Is it possible, multiple virtual projection centers in conjunction with multiple virtual projection levels in any convenient combination provided. For example, the virtual background of a virtual very far behind the virtual three-dimensional Image model arranged projection center on a first projection level be projected while an arrangement of many, very close to each other graduated objects projected through a second projection center in the virtual foreground will be no enlargements at these objects, but only a virtual shift of these Causes objects.

The choice of the virtual projection mechanisms or the number of viewing angles depends on a specific individual case, in particular on the image motif of the two-dimensional archetype, on the depth ratios interpreted in the archetype, on the desired and / or suppressible image effects and last but not least on the computational effort considered appropriate and the ultimately applied spatial imaging method for which the spatial image template is to be generated. In principle, however, any number of individual perspective images with any desired number of arbitrarily arranged virtual projection centers, virtual projection planes, viewing angles, etc., can be generated by the virtual three-dimensional image model 10 shown very simple embodiment only shows a non-representative, but only exemplary execution option.

In the 11a is a series of virtually generated by one of the previously described projection methods frames 208a to 208d from a virtual three-dimensional image model of the in 5a exemplified original image 200 shown. Although the virtual frames 208a to 208d black / white are shown in this embodiment, these are usually colored. In the single pictures 208a . 208b . 208c and 208d Above all, a different deformation of this image section can be recognized by comparing the flower structure shown in the upper part of the picture. This is created by the virtual projection of the virtual three-dimensional image model for the respective, in this embodiment, four virtual viewing angles.

11 shows one of the virtual frames 208a . 208b . 208c and 208d combined room image template 209 for an imaging process with spatial impression in conjunction with a magnified image detail 211 of the upper middle part of the image from the room image template 209 , The room image template 209 gets out of the frames 208a -D is combined with a depth effect according to the respective imaging method used.

The following are with reference to the 12a and 12b , or on the 13a to 13c exemplary two-dimensional image templates and their images by means of a monofocal lens grid described.

12a shows an exemplary two-dimensional archetype 200 in a series of image sections 361 is divided. The size of the individual image sections is in principle arbitrary and is essentially determined by the average size of the smallest closed image objects and the individual pixels. If it is assumed that clearly recognizable image structures lie in the foreground of the image, these must be detected by the image sections substantially as a unit, so that they are distinguishable from other structures and offer the viewing eye a sufficient Akkomodationsreiz. This means that with an increasingly small grid for a growing number of details Akkomodationsreize can be created that lead to a sense of depth in the viewer, unless the individual pixels, ie the image pixels are highlighted.

The 12a shows a matrix-shaped grid of substantially square image portions. Another division of the two-dimensional archetype 200 is however readily possible. It is expedient, inter alia, not shown here circular image sections in a hexagonal arrangement. The hexagonal arrangement of circular image sections offers the advantage that a given image section will have six immediate neighbors compared to the matrixed image partitioning, thus providing the accommodating eye with a more homogeneous transition from a first image section to the next environment of the image.

The picture sections 361 can contain preprocessed, in particular scaled, rotated or even mirrored over multiple axes image data, which are made primarily in view of the compensation of the imaging effect of the lens array in advance. In this case, the image sections form a mosaic actually present on the two-dimensional image template. Out 12a moreover, it shows that some image sections 361a contain a predominantly structurally poor image information, while some other image sections 361b are particularly structurally.

In the in 12a However, the grid of the image sections is initially not actually present in the original image itself and only appears through the lenticular grid placed above it. An example of this arrangement is shown in a side view in 12b shown. The two-dimensional image template appears on a display surface 370 , For example, the fluorescent surface of a picture tube or the liquid-crystalline matrix of a flat panel and is through a display surface 375 looked through. On the display surface 375 is the monofocal lenticular 360 arranged, for example, as a transparent, a series of matrix-like or hexagonal Fresnel lenses or zone plates containing film may be formed. The film itself adheres firmly to the surface of the display by adhesive adhesive forces, electrostatic forces or a transparent adhesive film. Each lens element 365 of the lens raster forms an image section underneath 361 so that this is caused by the magnification in front of or behind the image plane of the display 370 appears. Therefore, the lens elements 365 designed so that the display surface is either just before or behind the individual focal points of the lens grid.

In the 13a to 13c this is shown in more detail. The figures show an exemplary image detail 200a from the in 12a shown two-dimensional archetype 200 with those through the lenticular grid 360 or the local lens elements caused changes in the image detail.

The picture section 200a becomes an unchanged part of the two-dimensional archetype 200 out 12a formed on the display 370 is shown. In 13b becomes the image section 200a by an arrangement of four exemplary image sections 361 divided. The two left picture sections are included 361a each a rather featureless and diffuse image background information, while the right image sections 361 show a structurally rich content that is obviously in the foreground of the picture.

Each of these image sections will, as in 13c exemplified by a lens element 365 shown enlarged. In the in 13c shown exemplary representation, the magnification factor when using a lens element with focusing effect 365 about 1: 2. In this exemplary illustration, the left-hand parts of the picture yield 361a , which contain a diffuse structureless image background, even when magnified by the lenticular by their structurelessness a small Akkomodationsreiz, while the two right image sections 361b out 13c Contain structures that cause an accommodation of the eye on the image contents so represented. As a result, the picture contents of the right picture sections appear 361b out 13c much closer to the viewer than the contents of the left picture sections 361a , At an appropriate size of the individual image sections 361 The gaps created during imaging by the lenticular grid are compensated for and integrated by the action of the physiological visual perception apparatus.

In the embodiment of the 13a to 13c performs the mapping of the image sections 361 to a horizontally and vertically mirrored representation. Basically, there are two ways to counteract this effect. In a first procedure, the individual image sections of the two-dimensional archetype template are prepared in the successor of the previously mentioned image processing method, in particular scaled or mirrored horizontally or vertically, so that their image returns to the original output image. The strength of the preparatory scaling, or reflections, is derived on the basis of the magnification factor of the lens grid or the position of the objects to be displayed derived from the virtual three-dimensional image model and executed in advance on the image sections.

In a second possibility, which is applicable in particular for simple image motifs, such as characters or simple geometric structures on a uniform image background, the number, arrangement and size of the lens elements in the lenticular grid are chosen so that the image factors for the entire image are insignificant. Above all, this embodiment offers the advantage that in some cases computation-intensive image preparations can be dispensed with and the spatial image original without lenticular grids can be easily recognized. The picture 200 works without a monofocal lens grid as a normal two-dimensional image, while it appears staggered by the application of the lens grid in a depth effect, the depth effect by a mere

install the lenticular grid, so with very simple means, caused can be.

10

archetype data

20

read in the archetype data

30

To adjust the archetype data

40

caching the adapted one archetype data

50

between stored image data

60

optional Color channel / color distribution change

70

conversion in gray values

80

Edge detection method

81

dates of the image pixel

82

selection of the image pixel

83

read in the brightness value of the image pixel

84

Increase the brightness value

85

image pixels with increased brightness value

86

humiliate the brightness value

87

image pixels with reduced brightness value

88

Go to: next pixel

89

Picture menu for edge detection

90

Softening procedure

100

optional: Levels

110

fixed point definition

120

optional: set more checkpoint options

130

to save the grayscale mask

140

generated Grayscale mask

150

Distort the original image texture, creating the virtual three-dimensional Bildmo

dells, Create virtual frames

160

virtual Single images

170

combination the virtual frames

180

image data for spatial imaging

200

exemplary two-dimensional archetype

200a

image section

208a

first virtual single picture

208b

second virtual single picture

208c

third virtual single picture

208d

fourth virtual single picture

209

combined Space template

209a

enlarged section of a combined room image template

210

exemplary edge-marked image

220

exemplary edge-marked, softened image

230

exemplary Tonwertkorrigiertes soft-drawn image

239

Fixed point definition menu

240

fixed point defined image

241

histogram

242

Gray scale bar

243

indicators pointer

244

selection indicator

245

direct selection for brightness values

301

archetype, schematically

303

first object

304

second object

305

third object

306

accepted background

307

virtual picture frame with virtual depth levels

308

virtual frame

351

first virtual viewpoint with first viewing angle

352

second virtual viewing point with second viewing angle

360

monofokales lenticular

361

picture section

361a

low-structured image sections

361b

structurally rich sections of the picture

365

lens element

370

display

375 display surface

Claims (23)

Method for creating and displaying a spatial image template for imaging methods with spatial depth effects from two-dimensional image data, in particular image data from images, image sequences, video films and the like two-dimensional archetypes, characterized in that - on the basis of monocular original image data ( 10 ) determined image information based on a presumption-based spatial image depth grading virtual three-dimensional image framework ( 307 ), - the original image data on the virtual three-dimensional image framework ( 307 ) for generating a virtual three-dimensional image model ( 150 ), - the data of the virtual three-dimensional image model as a template for creating the spatial image template ( 209 . 209a ) be used. Method according to claim 1, characterized in that on the monocular original image data ( 10 ) for determining the image information, a method for edge detection ( 80 ) of the imaged objects with generation of an edge-marked image ( 210 ), wherein due to a determined edge richness different original image areas are assigned to different virtual depth planes, in particular a background and / or a foreground. Method according to claim 1, characterized in that on the original image data ( 10 ) is carried out to determine the image information, a method for determining the color information given Urbildareale, wherein the guess-based image depth gradation at least a first identified color information of a first virtual depth plane and a second color information of a second virtual depth plane are assigned. Method according to one of the preceding claims, characterized in that the method for edge detection ( 80 ) and the method for determining the color information individually and independently or in combination. Method according to one of claims 1 to 3, characterized in that on the edge-marked image ( 210 ) to reinforce and unify an edge-rich archetype realm as a blur ( 90 . 220 ) is applied. Method according to one of claims 1 to 5, characterized in that optionally a tonal value correction ( 100 ) of the edge-marked image ( 210 ) he follows. Method according to one of claims 1 to 6, characterized in that on the basis of the softened and / or additionally tonwertkorrigierten edge-marked image ( 210 . 220 ) based on the tone value of a pixel assignment of a relevant image section to a virtual depth level ( 303 . 304 . 305 . 306 . 307 ) is performed. Method according to one of the preceding claims, characterized in that in a fixed point definition ( 110 ) a limitation of the color and / or tone values to a predetermined value and a virtual pivot of the later generated virtual single views is determined. Method according to one of the preceding claims, characterized in that optionally a predefined color and / or brightness value of an image pixel has a predefined virtual depth plane ( 303 . 304 . 305 . 306 . 307 ). Method according to one of the preceding claims, characterized characterized in that defined image sections, in particular the image edge and / or center of the image a predetermined virtual Depth level is assigned. Method according to one of the preceding claims, characterized in that for generating the virtual three-dimensional image model, the virtual three-dimensional image framework ( 307 ) as one corresponding to the virtual depth planes ( 303 . 304 . 305 . 306 . 307 ) generates deformed virtual network structure and the two-dimensional archetype is adapted in a mapping process as a texture to the deformed network structure. Method according to claim 1 and 11, characterized in that of the virtual three-dimensional image model from a series of virtual observation angles ( 351 . 352 ) a series of virtual images representing the views of the virtual three-dimensional image model ( 208a . 208b . 208c . 208d . 308 ) are generated in which the image sections of the original image corresponding to a defined depth plane ( 200 . 301 ) are shifted and / or distorted according to the virtual viewing angle. Method according to one of the preceding claims, characterized in that the virtual single images ( 208a . 208b . 208c . 208d . 308 ) according to an algorithm for generating a spatial image template suitable for the imaging method with additional spatial effect ( 209 . 209a ) be combined. A method according to claim 1, characterized in that for creating the spatial image template ( 209 . 209a ) image processing of individual image areas of the original image, in particular a scaling and / or rotating and / or mirroring, executed and the resulting spatial image template by means of an overlying monofocal lens grid ( 360 ) is shown. Method according to claim 14, characterized in that the two-dimensional archetype ( 200 ) without an image processing by the monofocal lens grid ( 360 ), the two-dimensional archetype ( 200 ) forms the spatial image template for the display by the monofocal lenticular grid. Apparatus for displaying a spatial image template, characterized by a two-dimensional archetype image ( 200 ) as a two-dimensional image original and a monofocal lens grid ( 360 ). Apparatus according to claim 16, characterized in that the two-dimensional image template of a mosaic of the grid structure of the lenticular grid ( 360 ) associated image sections ( 361 . 361a . 361b ), wherein essentially one image section in each case forms an imaging object for essentially one respective lens element ( 365 ) of the monofocal lens grid. Device according to one of claims 16 or 17, characterized in that in a first embodiment the image sections ( 361 . 361a . 361b ) by substantially unchanged image components of the two-dimensional image template ( 200 ) are. Device according to one of claims 16 or 17, characterized in that in a further embodiment the image sections ( 361 . 361a . 361b ) for compensating the imaging effects of the lenticular grid ( 360 ) are scaled and / or mirrored and / or rotated. Device according to one of claims 16 to 19, characterized in that the two-dimensional image template ( 200 ) on a display ( 370 ) and the lenticular ( 360 ) on the surface ( 375 ) of the display is attached. Device according to one of claims 16 to 20, characterized in that the lenticular grid ( 360 ) is designed as a grid-like and adhering to the display surface Fresnel lens assembly. Device according to one of claims 16 to 20, characterized in that the lenticular grid ( 360 ) as a grid-like, adhering to the display surface zone plate assembly is executed. Device according to one of claims 16 to 20, characterized in that the lenticular grid ( 360 ) is designed as a grid-like, adhering to the display surface conventional convex lens arrangement.