Digital image generation using capture support data

Digital image generation through use of capture support data is described. In one example, an image capture device is configured to obtain capture support data from an imaging support system via a network through inclusion of a pre-capture system. The pre-capture system, for instance, is configured to obtain capture support data from an imaging support system via a network. The capture support data is configured for use by digital image processor along with raw image data received from an image sensor to generate a digital image, e.g., that is configured for rendering.

BACKGROUND

Digital image generation has become an increasing part of a user's everyday life as a direct result of exposure to a wide range of devices that include this functionality. This includes exposure to dedicated image capture devices as well as image capture devices incorporated as part of mobile phones, tablets, personal computers, and so forth. Because of this, designers and manufacturers of image capture devices continually strive to expand functionality available via these image capture devices to further differentiate these devices from each other.

One example of this is to include image editing functionality as part of a digital image processor of the image capture device. Therefore, generation of the digital image by the digital image processor into a ready-for-rendering format (e.g., for rendering by a display device, printer) may also include editing of the image, e.g., high dynamic range (HDR) imaging, noise removal, and so forth. To do so, conventional image capture devices have been designed to generate the digital image through use of a “closed system”.

However, a result of the editing as part of the actual generation of the digital image is that subsequent image editing and processing techniques are limited to access of this already edited version of the digital image. Consequently, subsequent image editing techniques in this conventional example are forced to address not only how the image was captured but also editing that may be performed as part of this capture. Because of the use of the closed-system in conventional techniques, however, knowledge of how the editing is performed may not be readily available. Although techniques have been developed to save an image in a raw data format, these techniques thus force the user into an “either or” scenario to choose between access to the expanded functionality made available by the image capture device or forgo this access altogether and use the raw data format.

SUMMARY

Digital image generation through use of capture support data is described. In one example, an image capture device is configured to obtain capture support data from an imaging support system via a network through inclusion of a pre-capture system. The pre-capture system, for instance, is configured to obtain capture support data from an imaging support system via a network. The capture support data is configured for use by digital image processor along with image data received from an image sensor (e.g., raw image data from a charge-coupled device) to generate a digital image that is configured for rendering. Other examples are also contemplated in which image data is processed that is in a renderable form.

In this way, the capture support data may be used to supplement and guide processing of the raw image data yet still take advantage of functionality that may be provided “internally” by the digital image processor to generate the digital image. The capture support data may be used to support a variety of functionality, including object removal, hole filling, may specify settings used to capture the image data, color palettes, lighting effects, filters, saturation, and so forth. In this way, the digital image processor is provided which an increased variety of data that is not available using conventional techniques through inclusion of the pre-capture system.

DETAILED DESCRIPTION

Overview

Techniques and systems are described in which capture support data is used to supplement or guide processing of image data (e.g., raw image data) into a digital image that is configured for rendering, e.g., by a display device, printer, and so forth. In this way, availability of image processing techniques by an image capture device may be expanded and yet preserve functionality made available by a “closed system” that may be specific to particular image capture devices, e.g., noise removal, HDR support, and so forth.

In one example, the image capture device includes a pre-capture system. The pre-capture system is configured to obtain capture support data that is usable to supplement and/or guide generation of a digital image from image data, e.g., raw image data obtained from an image sensor of the image capture device. As a result, the capture support data is provided “upstream” of the digital image processor in this example. This may be contrasted with conventional techniques that are limited to image editing that is performed as part of the generation of the digital image and/or after generation of the digital image by the digital image processor.

Image capture device manufacturers and designers, for instance, typically design the image capture device as an “image pipeline” that includes components to focus light (e.g., a lens and aperture), convert the light into an analog signal (e.g., an image sensor), convert the analog signal into a digital signal as raw image data (e.g., an analog/digital converter), and then generate a digital image that is configured for rendering through use of a digital image processor, e.g., a microcontroller, digital signal processor, or imaging core. As part of generating the digital image, the digital image processor may also perform one or more image editing techniques, e.g., generate the digital image as employing a high dynamic range, noise removal, and so forth. Conventional image editing techniques, however, are limited to access of this edited form of the digital image or a raw data format of the digital image in which editing has not been performed and is not configured for rendering.

Accordingly, a pre-capture system is described that is configured to obtain capture support data that may be used along with raw image data as part of generating a digital image that is configured for rendering. In this way, the capture support data may expand data available to the digital image processor as part of generating the digital image. This may also enable the techniques to take advantage of existing image editing functionality of the digital image processor, even when part of a “closed system.”

Capture support data may be configured in a variety of ways to support a variety of functionality as part of generation of the digital image, e.g., into a form configured for rendering. The capture support data, for instance, may include data that is also in a raw image format to supplement the raw image data captured by the image sensor, such as to support object removal, hole filling, patch-based image processing techniques, noise removal, and so forth. For example, the capture support data may provide support for removal of clouds from the digital image of an image scene based on another digital image of the same image scene that does not include clouds.

In another example, the capture support data is configured to guide the generation of the digital image. Examples of which include capture support data that specifies image processing functionality employed for editing similar digital images (e.g., color palettes, filters, color saturation, composition functionality), settings employed by other image capture devices to capture similar digital images (e.g., lens and shutter speeds), and so forth. This data may then be used to specify image editing functionality to be employed as part of generating the digital image by the digital image processor into a form that is fit for rendering. In this way, the pre-capture system may expand functionality that is available to the digital image processor over conventional techniques that are limited to processing of the digital image after the image has already been generated. The capture support data may thus be configured as generic or specific to a given image scene, e.g., specific instructions based on image data of the image scene.

In a further example, the capture support data is obtained via a network to guide generation of a digital image before receipt of a user input to initiate capture of the digital image. The pre-capture system, for instance, may obtain the capture support data to guide generation of the digital image before or after processing by a digital image processor. As a result, functionality used to generate the digital image may be expanded even before a user decides to capture the image. Further discussion of these and other examples is included in the following sections and shown in corresponding figures.

Example Environment

FIG. 1is an illustration of a digital medium environment100in an example implementation that is operable to employ pre-capture techniques described herein. The illustrated environment100includes a computing device102and an imaging support system104that are communicatively coupled, one to another, via a network106, e.g., the Internet. Computing devices that implement the computing device102and imaging support system104may be configured in a variety of ways.

A computing device, for instance, may be configured as a desktop computer, a laptop computer, a mobile device (e.g., assuming a handheld configuration such as a tablet or mobile phone as illustrated), and so forth. Thus, the computing device may range from full resource devices with substantial memory and processor resources (e.g., personal computers, game consoles) to a low-resource device with limited memory and/or processing resources (e.g., mobile devices). Additionally, although a single computing device is shown, a computing device may be representative of a plurality of different devices, such as multiple servers utilized by a business to perform operations “over the cloud” as illustrated for the imaging support system104and as further described in relation toFIG. 7.

The digital medium environment100is further illustrated as including an image capture device108as part of the computing device102that is configured to generate a digital image110. The digital image110is illustrated as stored in storage112, e.g., a computer-readable storage medium, database, and so forth. Other examples are also contemplated, such as implementation of the image capture device108as a standalone device, i.e., a dedicated digital camera.

The image capture device108includes a pre-capture system114that is representative of functionality to communicate with a support manager module116of an imaging support system104via the network106. As part of this communication, the pre-capture system114is configured to obtain capture support data118that is usable to supplement and/or guide generation of the digital image110by the image capture device108, e.g., into a form configured for rendering or edit a form already configured for rendering.

The image capture device108, for instance, may be used to capture a digital image110of an image scene120that includes the Eiffel Tower122and a cloud124. As part of capturing this digital image110, capture support data118is collected by the pre-capture system114, which may be performed even before a user “presses a button” to initiate capture of the digital image110. The capture support data118may then be used as part of generating the digital image110from raw image data collected from an image sensor of the image capture device108. In the illustrated example, this is used to remove the cloud from the digital image110as rendered126by a display device128. In this way, the capture support data118may be used as part of generation of the digital image110itself, and thus supports functionality as part of “pre-capture” of the digital image110. A variety of other configurations of capture support data118are also contemplated, further discussion of which is included in the following sections.

In general, functionality, features, and concepts described in relation to the examples above and below may be employed in the context of the example procedures described in this section. Further, functionality, features, and concepts described in relation to different figures and examples in this document may be interchanged among one another and are not limited to implementation in the context of a particular figure or procedure. Moreover, blocks associated with different representative procedures and corresponding figures herein may be applied together and/or combined in different ways. Thus, individual functionality, features, and concepts described in relation to different example environments, devices, components, figures, and procedures herein may be used in any suitable combinations and are not limited to the particular combinations represented by the enumerated examples in this description.

FIG. 2depicts an example system200showing an image processing pipeline of the image capture device108in greater detail as including the pre-capture system114. The image processing pipeline begins with at least one lens202(e.g., and associated variable diaphragm) that is used to focus light204onto an image sensor206. In one example, the image capture device108includes dual lenses202and image sensors206, such as to support different focal lengths, parallax, and so forth. The image sensor206is configured to generate an analog signal208responsive to exposure to light204, e.g., as a CCD or CMOS sensor. This analog signal208is then converted by an analog/digital converter210into raw image data212, e.g., from a single image sensor206or multiple image sensors as part of a dual-lens system.

Raw image data212is a camera file format that contains minimally processed data from the image sensor206. The raw image data212, for instance, is not yet processed and thus is not configured for rendering, e.g., for display, printing, and/or editing with a bitmap graphics editor. Thus, raw image data212is also considered a “digital negative” in that the negative is not directly usable as a digital image, but has the information used to create the digital image.

The raw image data212, for instance, may have a wider dynamic range or color gamut than a format used by the digital image110generated from this data. This is a result of capture by the raw image data212of radiometric characteristics of the image scene120, i.e., physical information about light intensity and color of the image scene120. As part of this, the raw image data212may store information accordingly to a geometry of photo-receptive elements of the image sensor206rather than as points (e.g., pixels) in the resulting digital image110.

The raw image data212is illustrated in this example as being provided to the pre-capture system114. The pre-capture system114includes a pre-capture processing module214that is representative of functionality implemented at least partially in hardware (e.g., an integrated circuit and memory) to obtain capture support data216from a support manager module116of an imaging support system104via a network106. The pre-capture processing module214, for instance, may form a request that is communicated to the imaging support system104. In response, the support manager module116generates capture support data216, which may include location of the capture support data216from memory, creation of the capture support data216, and so forth. The request, for instance, may be based on the raw image data212itself, characteristics of a geographic location at which the image capture device108is disposed, and so forth. Thus, the capture support data216may also take a variety of forms as further described below.

The raw image data212and the capture support data216are then provided to a digital image processor218, e.g., a digital signal processor, microcontroller, CPU of the image capture device108, and so forth. The digital image processor218includes an image processing module220that is representative of functionality to generated the digital image110from the raw image data212. As part of this, the image processing module220may also leverage capture support data216, such as to guide generation of the digital image110or supplement the raw image data212.

The capture support data216, for instance, may describe settings, color pallets, color saturation, and so forth used to capture other digital images and thus guide image processing functionality used to edit the digital image as part of generation from the raw image data212. In another instance, the capture support data216is used to supplement the raw image data212, such as through configuration in a raw image format that together is used to generate the digital image110as further described in relation toFIG. 3.

The digital image110, once generated, is illustrated as being output, e.g., for storage in a storage device112, rendering by a display device126, and so forth. As previously described, the digital image110is generated by the digital image processor218into a form ready for rendering, e.g., as a JPEG, TIFF, and so forth. Thus, in this example the capture support data216is employed to support editing and transformation of the digital image110even before the digital image110is generated, and thus is also referred to as use in “pre-capture” of the digital image.

In one example, the pre-capture system114is configured to form a request for capture support data216and even obtain the capture support data216before receipt of an input from a user to initiate the capture and generation of the digital image110. The image capture device108, for instance, may be associated with a user input device222that is configured to provide a capture input224to initiate capture of the digital image110, e.g., a physical button, a virtual button displayed by the display device126, and so forth. Even before “pressing the button,” the pre-capture system114may collect data describing characteristics of a physical environment, in which, the image capture device108is disposed (e.g., a geographic location, amount of light, etc.), collect raw image data212that describes objects included in the physical environment that is not yet rendered by the image capture device108, and so forth. This may thus support increased temporal and computational efficiency and real time generation of the digital image110by the digital image processor218that employs the capture support data216.

FIG. 3depicts an example implementation in which capture support data216is used to supplement raw image data212as part of generating a digital image110by a digital image processor218. In this example, the raw image data212is taken of an image scene120that includes the Eiffel Tower and a cloud124. Capture support data216is also obtained of an image scene302that includes the Eiffel tower122, but not the cloud124.

In one example, the pre-capture system114obtains the capture support data212based on a characteristic of a physical environment (e.g., a geographic location), through identification of an object included in the raw image data212by the imaging support system104, and so on. The pre-capture system114, for instance, may determine a current geographic location and “pre-fetch” the capture support data212even before a user removes the image capture device108from a pocket to generate the digital image110. Thus, as previously described the capture support data212may be obtained before, after, or at a time of capture of the raw image data212by the image capture device.

Thus, in this example the capture support data212is also configured according to a raw image format to supplement the raw image data212collected by the image sensor206of the image capture device108. In this way, the capture support data212is obtained from a source that is external to the image capture device108(e.g., the imaging support system104) to supplement generation of the digital image110into a form that is configured for rendering.

In another example, the capture support data216is configured to supplement the raw image data212as part of interpolation in a manner similar to high dynamic range (HDR) images are captured, but through use of an external source. The capture support data216, for instance, may be configured to address exposure, contrast, lighting and so forth in combination with the raw image data212to form the digital image110. Thus, the capture support data216may be combined (e.g., interpolated with) the raw image data212to increase a likelihood that a resulting digital image110is visually pleasing. This may include use of a single or multiple instances of raw image data212and/or capture support data216, e.g., a “burst” of raw image data212, multiple examples of capture support data216, and so forth. As a result, the capture support data216may be used to supplement the raw image data212from a source that may provide examples from different locations, at a different moment in time (e.g., for lighting issues), etc. Additional examples are described in the following discussion and shown in corresponding figures.

FIG. 4depicts an example implementation400in which capture support data118is obtained by the pre-capture system114of the image capture device108via a network106. To begin, the pre-capture system114forms a first communication402that is communicated over the network106to the support manager module116of the imaging support system104. A request reception module404, implemented at least partially in hardware of a computing device, receives this first communication402and from it extracts request data406. The request data406may be configured to request a variety of different types of capture support data118.

The request data406, for instance, may specify characteristics of a physical environment, in which, the image capture device108is disposed. This may include a geographic location obtained through use of a global positioning system, cell tower triangulation, Wi-Fi access, and so on. Other characteristics of a physical environment include lighting conditions, time-of-day, calendar day, direction at which the image capture device108“is facing” (e.g., through use of a compass), altitude, and so forth.

The request data406may also specify settings used by the image capture device108to collect the raw image data212, e.g., F-stop, shutter speed, filters, and so forth. The request data406may also be based on the raw image data212itself, e.g., include a down-sampled version of the raw image data, identify objects or materials in the image scene120, and so forth.

The request data406is then employed by a support data location module408(e.g., and corresponding machine learning module410) to generate capture support data118, which is illustrated as included in a storage device412. The machine learning module410, for instance, may employ a model that is generated to support the different types of requests and corresponding capture support data118.

As shown in an example system500ofFIG. 5, for instance, the machine learning module410includes a model training module502configured to generate models504using machine learning, e.g., through use of a neural network. The machine learning module410also includes a model use module506that is configured to use the models504to generate capture support data118as corresponding to the request data406extracted from the first communication402.

The model training module502may train the models504in a variety of ways. In one illustrated example, the modeling training module502receives training data from a content creation system508and/or a content sharing system510. The content creation system508is configured to provide content creation functionality that is usable to edit digital images and/or raw image data, which is represented by the creation manager module512.

A user of computing device102, for instance, may interact with the content creation system508via a network106to edit data, e.g., digital images generated by an image capture device. A result of monitoring of this interaction by the creation manager module512is captured as image transformation data514that then describes which image editing operations are performed to achieve “good” digital images. This determination of what is “good” may be performed manually (e.g., through receipt of user inputs via a user interface after display of training digital images) or automatically, e.g., through a model learned via machine learning. The image transformation data514may then be used to guide which editing operations are to be performed for similar digital images and even how this editing is to be performed. Therefore, in this example the models504are used by the model use module506to generate capture support data118to guide this editing as part of generation of the digital image110.

Similar model training techniques may also be implemented by the model training module502based on image capture setting data516that describes how digital images are captured by image capture devices, e.g., images available via the content creation system508, stock digital images518available via a storage device520of a content sharing system510(e.g., a stock-image database), and so forth. The image capture setting data516, for instance, may be associated as part of metadata of a digital image, e.g., the stock digital images518. The image capture settings data516may then be correlated with image transformation data514that also describes how these images are subsequently edited. Therefore, this combination may also be used to train models504which are then used to generate capture support data118based on the image capture settings used to capture raw image data212as well as how that image was subsequently modified to achieve a “good” result.

Thus, in the above examples the capture support data118is used to guide subsequent editing as part of generation of the digital image110. Other examples of use of the capture support data118as a guide include use that is based on identification of a particular material within the image scene120(e.g., metal and precomputation of lighting profiles), color profiles, suggestions of composition, and so forth.

The imaging support system104may also be configured to generate capture support data118that is to be used to supplement the raw image data212. The support manager module116, for instance, may or may not use machine learning to generate raw format data that corresponds to an image scene120captured by the raw image data212. As described in relation toFIG. 3, for instance, this may be used to support a variety of functionality, such as object removal as illustrated, hole filing, and so forth. Thus, in this example the raw format data522obtained “outside” of the image capture device108may be composited with the raw image data212to achieve a desired image editing result.

Returning again toFIG. 4, the generated capture support data414is provided from the support data location module408to a communication generation module416. The communication generation module416is configured to form and transmit a second communication418via the network106to the pre-capture system114for use by the image capture device108in generating the digital image110, e.g., to guide or supplement editing as part of generation of the digital image110. In this way, functionality of the image capture device108may be expanded to support image editing even before the digital image110is generated into a form configured for rendering.

Example Procedures

FIG. 6is a flow diagram depicting a procedure in an example implementation in which a digital image is generated in a form that is configured for rendering based on raw image data and capture support data. Image data (e.g., raw image data212) is collected through use of an image sensor206of an image capture device (block602). Light204, for instance, may be focused by a lens202onto the image sensor206, which causes generation of an analog signal208that is then converted to raw image data212by an analog/digital converter210. Other examples are also contemplated, such as through use of image data that is configured for rendering, such as JPEG, TIFF, and so forth.

Capture support data216is obtained by a pre-capture system114of the image capture device108. The capture support data216is available remotely via a network106(block604). For example, a communication (e.g., first communication402) is formed for communication to an imaging support system104(block606) by the pre-capture system114. The capture support data118is received responsive to the communication (block608), e.g., as a second communication418via the network106.

A digital image110is generated by a digital image processor218of the image capture device108through processing the image data (e.g., raw image data212) based at least in part of the capture support data216(block610). The capture support data216, for instance, may be used to guide or supplement editing of the raw image data212as part of generating the digital image110into a renderable form. A variety of other examples are also contemplated as discussed above, such as to further edit digital images that are in a renderable form before receipt of an input from a user to initiate capture of the digital image, e.g., for output as a preview image in a viewfinder, display device of a mobile phone, etc.

Example System and Device

FIG. 7illustrates an example system generally at700that includes an example computing device702that is representative of one or more computing systems and/or devices that may implement the various techniques described herein. This is illustrated through inclusion of the image capture device108. The computing device702may be, for example, a server of a service provider, a device associated with a client (e.g., a client device), an on-chip system, and/or any other suitable computing device or computing system.

The example computing device702as illustrated includes a processing system704, one or more computer-readable media706, and one or more I/O interface708that are communicatively coupled, one to another. Although not shown, the computing device702may further include a system bus or other data and command transfer system that couples the various components, one to another. A system bus can include any one or combination of different bus structures, such as a memory bus or memory controller, a peripheral bus, a universal serial bus, and/or a processor or local bus that utilizes any of a variety of bus architectures. A variety of other examples are also contemplated, such as control and data lines.

The computer-readable storage media706is illustrated as including memory/storage712. The memory/storage712represents memory/storage capacity associated with one or more computer-readable media. The memory/storage component712may include volatile media (such as random access memory (RAM)) and/or nonvolatile media (such as read only memory (ROM), Flash memory, optical disks, magnetic disks, and so forth). The memory/storage component712may include fixed media (e.g., RAM, ROM, a fixed hard drive, and so on) as well as removable media (e.g., Flash memory, a removable hard drive, an optical disc, and so forth). The computer-readable media706may be configured in a variety of other ways as further described below.

Combinations of the foregoing may also be employed to implement various techniques described herein. Accordingly, software, hardware, or executable modules may be implemented as one or more instructions and/or logic embodied on some form of computer-readable storage media and/or by one or more hardware elements710. The computing device702may be configured to implement particular instructions and/or functions corresponding to the software and/or hardware modules. Accordingly, implementation of a module that is executable by the computing device702as software may be achieved at least partially in hardware, e.g., through use of computer-readable storage media and/or hardware elements710of the processing system704. The instructions and/or functions may be executable/operable by one or more articles of manufacture (for example, one or more computing devices702and/or processing systems704) to implement techniques, modules, and examples described herein.

The cloud714includes and/or is representative of a platform716for resources718. The platform716abstracts underlying functionality of hardware (e.g., servers) and software resources of the cloud714. The resources718may include applications and/or data that can be utilized while computer processing is executed on servers that are remote from the computing device702. Resources718can also include services provided over the Internet and/or through a subscriber network, such as a cellular or Wi-Fi network.

The platform716may abstract resources and functions to connect the computing device702with other computing devices. The platform716may also serve to abstract scaling of resources to provide a corresponding level of scale to encountered demand for the resources718that are implemented via the platform716. Accordingly, in an interconnected device embodiment, implementation of functionality described herein may be distributed throughout the system700. For example, the functionality may be implemented in part on the computing device702as well as via the platform716that abstracts the functionality of the cloud714.

CONCLUSION