29 results about "Bokeh" patented technology

This disclosure provides systems, methods, and devices for image signal processing that support adjusting a Bokeh effect in image data. In a first aspect, a method of image processing includes receiving a first user input specifying a first depth of focus. A camera is configured with a first aperture size of a plurality of aperture sizes of the camera that is nearest a second aperture size that corresponds to the first depth of focus. The first aperture size is smaller than the second aperture size. Image data representing a scene is received that is captured with the first aperture size of the camera. First modified image data is determined by applying a first blur kernel to the image data. The first modified image data represents the scene at the depth of focus corresponding to the second aperture size. Other aspects and features are also claimed and described.

The invention provides a bokeh effect rendering method and system, and the method comprises the steps: obtaining a target physical depth map corresponding to an original image for different input sources; performing image preprocessing on the original image and the target physical depth image to obtain a color image, a depth image and camera parameters; processing the depth map in combination with the camera parameters, and calculating to obtain a CoC map; determining the texture information of the TileInfoMap sampling radius in the CoC image, and determining the texture information of the TileInfoMap sampling radius in the CoC image; and carrying out rendering by utilizing the color image, the CoC image, the TileInfoMap sampling radius texture information and DiapragmMap texture information input by a user, so as to obtain a result image with a bokeh effect. According to the invention, the virtual quantity calculation which is closer to physics is provided, the influence of physical parameters such as an aperture, a focusing distance, a lens focal length and a picture on the virtual quantity is truly restored, meanwhile, the influence of the change of the lens focal length on a field angle is fully considered, and a vivid rendering effect is realized.

The invention relates to the technical field of computer vision, and discloses a variable aperture scatter rendering method and system. The method comprises the following steps: firstly, acquiring a full-focus input image, a depth map and a target aperture parameter; inputting the full-focus input image into a neural network of an encoder-bottleneck layer-decoder structure to extract features; inputting the depth map and the target aperture parameter to an adaptive routing prompt module to generate a prompt vector; in an encoder stage, performing differentiation processing on the features through adaptive spatial routing by using a prompt vector, and inhibiting inter-region interference in combination with a depth map-based layered sparse attention mechanism; in a bottleneck layer and decoder stage, channel modulation is carried out by using a prompt vector and jump connection features are fused, and image details are gradually recovered; and finally, fusing the output scatter-scene residual image with the full-focus input image to generate a target aperture scatter-scene image. According to the method, the controllability, the boundary naturalness and the detail fidelity of boarder rendering are effectively improved.

The invention discloses an image processing method and device, and belongs to the field of computing camera shooting. The method comprises the following steps: acquiring a to-be-processed image and a blurring parameter of the to-be-processed image; inputting the to-be-processed image and the blurring parameters into a blurring rendering model for blurring rendering processing to obtain a bokeh image of the to-be-processed image output by the blurring rendering model; wherein the blurring rendering model is a model obtained by performing fine tuning training on a pre-training diffusion model based on multiple groups of training data, each group of training data comprises input data and label data of the input data, and the input data comprises a full-focus image sample and a blurring parameter of the full-focus image sample; the label data comprises a bokeh image of a full-focus image sample, and the pre-training diffusion model adopts an optical self-attention mechanism based on computational optics.

An electronic device and method are disclosed. An electronic device includes a memory and a processor that implements the method, the method including obtaining image data of an image, setting a region of interest and a background region in the image using depth information, both including one or more sub-regions, the method further includes determining respective bokeh characteristics of the one or more first sub-regions and the one or more second sub-regions based on the first characteristic criterion and the second characteristic criterion, respectively, and processing the image to apply a bokeh effect to the plurality of pixels based on the respective bokeh characteristics of the one or more first sub-regions and the one or more second sub-regions.

Provided may be a method for: acquiring a luminance map having a higher bit depth than an input image; determining a distance difference between a reference pixel in focus and the current pixel in the input image by using a depth map corresponding to the input image; determining the size of a geometric kernel corresponding to the current pixel by using the distance difference between the reference pixel and the current pixel; and generating and outputting a bokeh image corresponding to the input image by using the luminance differences between the current pixel and neighboring pixels in the geometric kernel having the determined size and luminance weights based on the luminance map.

According to one embodiment, an electronic device may include at least one processor and at least one camera. The at least one processor may acquire an image through the at least one camera. The at least one processor may generate a depth map including depth data corresponding to a plurality of objects. The at least one processor may receive a user input for identifying an object that will not be blurred from among the plurality of objects. The at least one processor may identify an improvement area on the basis of the object and the depth map corresponding to the user input. The at least one processor may identify a focus area on the basis of the object and the depth map corresponding to the user input. The at least one processor may generate an output image on the basis of a synthesis of the focus area and a portion of the image excluding the focus area.

The present application relates to a kind of video monitoring image quality enhancement methods under adverse weather conditions, comprising the following steps: construct the blur rendering model based on generative adversarial network, then train and verify model;Blur rendering model includes discriminator, residual dense network, feature fusion module and generator;Initial image input blur rendering model is first judged by discriminator whether real sample or generated image, then, initial image input residual dense network, feature information of input image is extracted step by step, foreground target feature is strengthened, obtain multiple feature maps, generate feature fusion map after the fusion of multiple feature maps, generator adds random noise to feature fusion map, output generated image;Image denoising restoration model based on Unet model is constructed, and model is trained and verified after;Generated image is input into image denoising restoration model, and clear restored image is output.The present application has the advantages that foreground target information can be enhanced, and the authenticity and accuracy of image recovery can be ensured.

A residual aberration controller arranged in the optical path of an image-forming light beam to create an aesthetic effect in an otherwise sharp image by selectively introducing residual aberrations into the wavefront of the image-forming light beam. The residual aberration controller is adjustable between a first configuration that provides either no substantial change or a relatively small aesthetic change to the otherwise sharp image and a second configuration that provides a substantial change to the sharp image to create the aesthetic effect. Aesthetic effects can include, to varying degrees, flare, bokeh, image softening, anamorphic and related effects that are desirable in certain imaging applications but that are difficult to produce in a quick and reversible manner. The residual aberration controller can be combined with almost any type of objective lens to achieve aesthetic imaging effects quickly, affordably and reversibly by a simple adjustment and without defocus.

The present application relates to the technical field of computer vision, and discloses a variable aperture bokeh rendering method and system. The method first acquires a full-focus input image, a depth map thereof and a target aperture parameter; extracts features of the full-focus input image by inputting the full-focus input image into a neural network of an encoder-bottleneck layer-decoder structure; inputs the depth map and the target aperture parameter into an adaptive routing prompt module to generate a prompt vector; in the encoder stage, the prompt vector is used to differentially process the features through adaptive spatial routing, and a layered sparse attention mechanism based on the depth map is combined to suppress inter-region interference; in the bottleneck layer and the decoder stage, the prompt vector is used for channel modulation and fusion of the jump connection features to gradually restore image details; and finally, the output bokeh residual image is fused with the full-focus input image to generate a target aperture bokeh image. The present application effectively improves the controllability, boundary naturalness and detail fidelity of bokeh rendering.

Provided in the embodiments of the present application are a photographing method, an electronic device and a storage medium. The method can be applied to an electronic device that supports bokeh capturing, wherein the electronic device is, for example, a smart phone or a tablet computer. The bokeh capturing refers to performing depth calculation and portrait blurring processing on a captured image, and optionally further performing dynamic range fusion processing. The method may comprise: in response to a detected user operation acting on a bokeh capturing control, starting bokeh capturing and calling a camera apparatus to collect preview stream data of a photographing scene; determining statistical information of the photographing scene on the basis of the preview stream data; in response to the statistical information satisfying a mode switching condition, switching the bokeh capturing processing mode from a first processing mode to a second processing mode; and in response to a bokeh capturing instruction for the photographing scene, on the basis of the second processing mode, processing an image to be processed, so as to obtain a bokeh-captured image of the photographing scene. By using the embodiments of the present application, the power consumption of an electronic device can be reduced in a bokeh capturing scenario.

An electronic device and method are disclosed. The electronic device includes a memory and processor, which implements the method, including: obtaining image data for an image, set in the image a region of interest and a background region, using depth information, both including one or more sub-regions, determining respective bokeh characteristics for the one or more first sub-regions and the one or more second sub-regions based on a first characteristic criterion and a second characteristic criterion, respectively, and processing the image to apply a bokeh effect to the plurality of pixels based on the respective bokeh characteristics for the one or more first sub-regions and the one or more second sub-regions.

An electronic device is provided. The electronic device includes at least one camera, memory, including one or more storage media, storing instructions, and a processor communicatively coupled to the at least one camera and the memory, wherein the instructions, when executed by the processor, cause the electronic device to obtain an image via the at least one camera, generate a depth map including depth data corresponding to a plurality of objects, receive a user input for identifying an object not to be processed with blur processing among the plurality of objects, identify an improvement region based on the object corresponding to the user input and the depth map, identify a focus region based on the object corresponding to the user input and the depth map, and generate an output image based on a composite of the portion of the image where the focus region is excluded and the focus region.

The embodiment of the invention provides a bokeh fuzzy processing method and device, equipment, a storage medium and a product. According to the technical scheme provided by the embodiment of the invention, the background mask graph is determined according to the transparency graph of the to-be-processed image, the index calculation is performed on the background mask graph and the color value of each pixel point in the to-be-processed image to obtain the light source spread function, and the convolution mask is determined according to the light source spread function and the background mask graph. And performing mask convolution processing on the to-be-processed image according to the convolution mask and a preset convolution kernel to obtain a background blurred image, and performing fusion processing on the to-be-processed image and the background blurred image according to the transparency image to obtain a target blurred image. The unnatural fusion at the foreground and background junction is effectively reduced, the color leakage of pixel blurring at the foreground and background junction is reduced, the natural degree of the edge during the foreground and background fusion is improved, and the blurring effect of the scattered scene is effectively improved.

This application discloses an image generation method and apparatus, belonging to the field of artificial intelligence technology. An embodiment of the method includes: acquiring an original image; inputting the original image into a bokeh parameter prediction model to obtain a bokeh parameter map; performing bokeh processing on the original image based on the bokeh parameter map to generate an initial bokeh image; and inputting the initial bokeh image into a bokeh image generation model to obtain a target bokeh image.

A processor generates a depth map from two images, including high dynamic range (HDR) images. The processor receives one or more first images from a first image sensor, where the one or more first images have a first field of view (FOV) and a first resolution, and receives one or more second images from a second image sensor, where the one or more second images have a second FOV and a second resolution. The processor generates a first HDR image from the one or more first images, and performs tone alignment on the one or more second images based on the first HDR image to generate a second HDR image. The processor generates a depth map using the first HDR image and the second HDR image. The processor can use the depth map to apply a bokeh effect to the first HDR image.

Described methods and systems for achieving an optical bokeh effect by a camera supporting a computing device, such as a laptop computer. A measurement is performed as to focus spot position of a subject. The depth of field (DOF) of camera lens is determined. An offset as to the focus spot position is calculated such the background of the subject would be blurred to increase the optical bokeh effect. The offset is added to the focus spot position or to be more in focus to decrease optical bokeh in the background, to arrive at a focus spot position that supports the optical bokeh effect. The camera lens is adjusted for the new focus spot position.

An electronic device includes an image capture device configured to capture image sensor data in response to initiation of an image capture operation. The electronic device includes one or more processors and a display operable with the one or more processors. The one or more processors select saturated pixels of the image sensor data and determine a gain factor as a function of brightness values of pixels in the image sensor data. The one or more processors increase an intensity value of the saturated pixels by the gain factor to create scaled image sensor data, blur at least some of the scaled image sensor data by convolving a blur kernel with the scaled image sensor data to create altered image sensor data exhibiting a simulated bokeh effect and cause the display to present the altered image sensor data exhibiting the simulated bokeh effect.

The present invention relates to a semantic segmentation method based on background blur, which is implemented by embedding a BOKEH module in an existing FCN semantic segmentation network. The algorithm of the BOKEH module is described as #imgabs0##imgabs1#, where img(:,:,k) represents the pixel value size on the k channel of the image; σ represents the blur factor; R B* Represents the overall background rate of the training set; R B The background domain ratio (BGL) represents the background position information of the image. This semantic segmentation method based on background blurring (BOKEH) undergoes in-depth analysis and optimization of the dataset. Without changing the existing network architecture or increasing the data size, it effectively improves the network segmentation performance by embedding the background blurring module (BOKEH) into the existing FCN semantic segmentation network.

The utility model discloses an optical lens, which comprises a first lens, a second lens, a third lens, a fourth lens, a diaphragm, a fifth lens and a sixth lens which are sequentially arranged from an object side to an image side along an optical axis direction, the third lens and the fourth lens are glued to form a doublet lens; the first lens is provided with a convex surface and a concave surface and is installed in the forward direction or the reverse direction. When the first lens is installed in the forward direction, the convex surface faces the object side, and the concave surface faces the image side. When the first lens is reversely installed, the convex surface faces the image side, and the concave surface faces the object side. According to the optical lens, the first lens provided with the convex surface and the concave surface is installed in the forward direction or the reverse direction, the diaphragm and the multiple lenses are combined for cooperative imaging, the optical lens can have at least two imaging effects, standard imaging performance is provided through forward installation, and the conventional photographing requirement is met; the light propagation path is changed through reverse installation, so that background blurring light spots are radially diffused, and a unique out-of-focus bursting effect is formed.

This disclosure provides systems, methods, and devices for image signal processing that support adjusting a Bokeh effect in image data. In a first aspect, a method of image processing includes receiving a first user input specifying a first depth of focus. A camera is configured with a first aperture size of a plurality of aperture sizes of the camera that is nearest a second aperture size that corresponds to the first depth of focus. The first aperture size is smaller than the second aperture size. Image data representing a scene is received that is captured with the first aperture size of the camera. First modified image data is determined by applying a first blur kernel to the image data. The first modified image data represents the scene at the depth of focus corresponding to the second aperture size. Other aspects and features are also claimed and described.

This electronic device may comprise: at least one camera; a display; a memory storing instructions; and at least one processor including processing circuitry. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to: while a preview image obtained through the at least one camera is displayed through the display, receive a user input for setting a value of a virtual aperture; obtain a preview bokeh image on the basis of providing the value of the virtual aperture and the preview image to a bokeh model; and display the preview bokeh image through the display.

An image processing apparatus applies, to an input image, image restoration processing for correcting bokeh caused by a characteristic of an imaging optical system used to capture the input image. The image processing apparatus may further add a predetermined effect to a high luminance portion satisfying a predetermined condition in the input image to which the image restoration processing has been applied. The image processing apparatus has capabilities both correcting bokeh caused by an aberration in an optical system while keeping bokeh as photographic expression.

Described are methods and systems that determine bokeh ratio of a camera, such as a webcam in an information handling system. A focal point and bokeh point are determined for the camera. An image of a Siemens star chart (star chart) is captured by the camera at the bokeh point. The diameter of the captured image of the star chart and diameter of blur circle in the image of the star chart are measured. The ratio of the diameter of the blur circle to the diameter of the captured image of the star chart is correlated to the bokeh ratio of the camera.

A method for improving the stability of bokeh processing is disclosed. The method includes: acquiring an image, an autofocus region in the image, and a depth map; performing subject segmentation processing on the image to obtain a subject region indicating a target subject; extracting a depth value from the subject region from the depth map when the subject segmentation processing is successful, or extracting a depth value from the autofocus region from the depth map when the subject segmentation processing is unsuccessful but the autofocus operation is successful; determining a reference depth value based on the extracted depth value; and performing bokeh processing on the image based on the reference depth value. The depth map corresponds to the image.

The present invention relates to a method and device for simulating the imaging of a large-aperture lens. The method includes obtaining an original image; performing depth-of-field processing on the original image to obtain a depth-of-field map; calculating the radius of the circle of confusion in the original image according to the depth value of the depth-of-field map, determining the size of the circle of confusion, and enhancing the brightness of the circle of confusion through gamma correction to obtain a corrected image; performing bokeh blur processing on the corrected image according to preset bokeh parameters to obtain a bokeh-blurred image; and performing inverse gamma correction on the bokeh-blurred image to obtain a result image. The present invention uses a deep learning method to obtain the depth of a picture, does not rely on the original information of the picture, and can process pictures from various sources; nor does it rely on hardware devices and can independently run on different mobile devices to provide a bokeh effect, which is suitable for most picture editing; in addition, based on the depth map rather than foreground and background segmentation, the effect is more delicate and natural, and different intensities of bokeh effects can be observed in different depth regions of the picture.

The present disclosure provides a system, method, and device for image processing that supports enhancement of image effects, such as bokeh effects, applied in image processing. In a first aspect, a method of image processing includes determining a depth map corresponding to a first scene based on first image data and second image data captured with different aperture sizes, determining a focus map based on the depth map and a simulated aperture size different from the first aperture size and the second aperture size, and determining an output image frame based on the focus map, the first image data, and the second image data. Other aspects and features are also claimed and described.

An electronic device (300) according to various embodiments of the present document may comprise: a display (830); a plurality of cameras (310) disposed adjacent to each other and having different optical characteristics; a memory (820); and at least one processor (850) operatively connected to the display, the plurality of cameras, and the memory. The memory may store instructions that may be executed by the at least one processor, and when executed, instruct the electronic device to: determine a first zoom magnification related to image capturing; acquire a first image by using a first camera corresponding to the first zoom magnification from among the plurality of cameras; if the first zoom magnification belongs to a digital zoom section of the first camera, generate a cropped image by cropping a part of the first image on the basis of the first zoom magnification; and on the basis of optical characteristics of the first camera and optical characteristics of a second camera, determine a bokeh level to be applied to a background subject included in the cropped image at the first zoom magnification. Various other embodiments are possible.