Apple Inc.

Frederic Cao

Garrett M Johnson

Touraj Tajbakhsh

Jonathan P Ive

Alan C Dye

Andre Souza Dos Santos

Grant R Paul

Arian Behzadi

Cyrus Daniel Irani

Pavel Pivonka

Jeffrey A Brasket

Emilie Kim

Billy Sorrentino, Iii

Behkish J Manzari

Joseph A Malia

Philip G Lee

Yury Degtyarev

Suk Hwan Lim

Paul M Hubel

Daniel Trent Preston

Elliott B Harris

Chihsin Wu

Marek A Bereza

Johnnie B Manzari

Muge Wang

Wei Sun

Angelo M Alaimo

Kathrin Berkner Cieslicki

Gregory Guyomarc'h

Bosheng Zhang

Bryan Dang

Chong Chen

Marek Bareza

Elliot Harris

Caroline Hermans

Garett Johnson

Johnnie Behkish Manzari

Billy Sorrentino Iii

Billy Iii Sorrentino

The present disclosure generally relates to user interfaces. In some examples, the electronic device provides for transitioning between simulated lighting effects. In some examples, the electronic device applies a simulated lighting effect to an image. In some examples, the electronic device provides user interfaces for applying a filter to an image. In some examples, the electronic device provides for a reduced filter interface. In some examples, the electronic device provides a visual aid displayed in a viewfinder.

User interface camera effects

A light source module includes an array of illumination elements and an optional projecting lens. The light source module is configured to receive or generate a control signal for adjusting different ones of the illumination elements to control a light field emitted from the light source module. In some embodiments, the light source module is also configured to adjust the projecting lens responsive to objects in an illuminated scene and a field of view of an imaging device. A controller for a light source module may determine a light field pattern based on various parameters including a field of view of an imaging device, an illumination sensitivity model of the imaging device, depth, ambient illumination and reflectivity of objects, configured illumination priorities including ambient preservation, background illumination and direct/indirect lighting balance, and so forth.

Adaptive-flash photography, videography, and/or flashlight using camera, scene, or user input parameters

This disclosure relates to techniques for synthesizing out of focus highlighting effects in images in real-time. Digital single-lens reflex (DSLR) cameras and other cameras having wide aperture lenses typically capture images with a shallow depth of field (SDOF). So-called SDOF photography may be particularly fit for portrait photography, since it nicely emphasizes the subject, while essentially deemphasizing the background via blurring. Simulating this kind of blurring, particularly around background light sources, using a comparatively larger depth of field (LDOF) camera, may require a high dynamic range (HDR) image capture system, to accurately determine the color of background light sources, which are prone to saturation. However, small form-factor cameras having smaller lens apertures may not have the bandwidth or processing power to process full HDR images in real time. Thus, described herein are techniques to synthesize color accurate, out-of-focus background highlight regions in real-time for images captured by LDOF cameras.

Real-time synthetic out of focus highlight rendering

Embodiments relate to hue preservation post processing for highlight recovery of an input image. Intensity values for multiple color channels of a plurality of color channels of a pixel of the input image is determined using corresponding ratios of target hues for the plurality of color channels of the pixel, wherein the pixel has at least one color channel with an intensity above a predetermined threshold. A hue preserved value for a color channel of the plurality of color channels of the pixel is determined using intensity values determined for the plurality of color channels of the pixel and the target hues. A recovered version of the input image is generated by adjusting hue information of the pixel, using the hue preserved value for the channel of the plurality of color channels of the pixel.

Hue preservation post processing with early exit for highlight recovery

Hue preservation post processing for highlight recovery

This disclosure relates to the lightweight and efficient synthesis of shallow depth of field (SDOF) renderings. According to some embodiments, coarse focus information and semantic segmentation information may be leveraged to generate SDOF renderings in a 'live preview' or 'streaming' mode. Semantic segmentation may be defined as a process of creating a mask over an image, wherein pixels are segmented into a predefined set of semantic classes. Segmentations may include as many classes as are desired by a given implementation (e.g., a 'foreground' class and a 'background' class). In some embodiments, the rendering of synthetic SDOF images according to the techniques described herein may be completed using only a single camera of a device and without the use of dedicated depth-sensing technology (e.g., structured light cameras, stereo cameras, time-of-flight cameras, etc.), thereby allowing the SDOF rendering process to operate in a fashion that is not unduly time-, processing-, and/or power-intensive.

Shallow depth of field (SDOF) rendering

Embodiments relate to generation of hue maps for highlight recovery of an input image. An image having a plurality of color channels is obtained at a first resolution lower than a resolution of the input image. A hue for each color channel for each pixel is determined, using a pixel value for that color channel and pixel values for the plurality of color channels in the first image. Weights are determined for each pixel for each color channel, based on hues for the pixel and pixel values for the pixel in the first image. A plurality of candidate hue maps are generated, based on the weights and pixel values in the first image in a patch surrounding the pixel for the plurality of color channels.

Hue map generation for highlight recovery

Embodiments of the present disclosure can provide systems, methods, and computer-readable medium for providing virtual lighting adjustments to image data. A number of source images may be generated to individually depict solid colors of a color space (e.g., RGB color space). Virtual lighting adjustments associated with a virtual lighting mode may be applied to each source image to generate a corresponding target image. The source images and the target images may be utilized to train a model to identify pixel modifications to be applied to image data. The modifications may be associated with a virtual lighting mode. Subsequently, a user may obtain image data (e.g., an image or video) select a virtual lighting mode via an image data processing application. The previously trained model may be utilized to modify the image to apply the virtual lighting effects associated with the selected virtual lighting mode.

Techniques for providing virtual lighting adjustments utilizing regression analysis and functional lightmaps

Embodiments of the present disclosure can provide systems, methods, and computer-readable medium for providing virtual lighting adjustments to image data. A user interface for presenting and/or modifying image data may be provided via an electronic device. User input may be received that indicates a selection of a virtual lighting mode. Landmark points corresponding to a set of pixels of the image data may be identified based, at least in part, on depth measurement values of the set of pixels. One or more masks may be generated from the landmark points. One or more virtual lighting adjustments associated with the selected virtual lighting mode may be made to the image data using these masks (or the landmark points and an implied geometry of the landmark points). The adjusted/modified image may be presented to the user via the user interface at the electronic device.

Techniques for providing virtual light adjustments to image data

Embodiments of the present disclosure relate to highlight recovery of a high-resolution image using a single low-resolution image captured at a lower exposure. An example apparatus includes a hue target circuit that receives an input image at a high-resolution including at least one pixel with a clipped color channel. For example, the input image is a Blue sky image with a pixel having clipped Blue channel. The hue target circuit also receives a set of candidate hue maps having a pixel resolution lower than the high-resolution of the input image. The hue target circuit generates a target hue value for the at least one pixel using the pixel information of the set of candidate hue maps. The apparatus also includes a hue recovery circuit that generates a recovered version of the input image by adjusting hue information of the clipped color channel based on the generated target hue.

Highlight recovery in images

Growing community of inventors

Santa Clara, CA, United States of America

Frederic Cao