Abstract: This disclosure describes techniques for performing automatic synthetic shallow depth of field (SDOF) or so-called “portrait mode” suggestions for digital image capture. In particular, these techniques aim to solve the problem of letting users of digital image capture devices know when to turn on portrait image capture modes to capture aesthetically pleasing images. If, based on the application certain criteria, a currently-composed scene is detected to be “portrait worthy,” an icon or other indicator may be provided, e.g., on a user interface of the digital image capture device. According to some embodiments, once a scene has been determined to be portrait worthy, the digital image capture device may capture a subsequent image(s) with at least one additional data asset needed to render a captured image in a synthetic SDOF or portrait mode. This will allow users to convert their digital images into portrait mode images via digital image post-processing operations.

Abstract: In one implementation, a method includes obtaining an image. The method includes splitting the image to produce a high-frequency component image and a low-frequency component image. The method includes downsampling the low-frequency component image to generate a downsampled low-frequency component image. The method includes correcting color aberration of the downsampled low-frequency component image to generate a color-corrected downsampled low-frequency component image. The method includes upsampling the color-corrected downsampled low-frequency component image to generate a color-corrected low-frequency component image. The method includes combining the color-corrected low-frequency component image and the high-frequency component image to generate a color-corrected version of the image.

Abstract: In one implementation, a method includes obtaining an image. The method includes splitting the image to produce a high-frequency component image and a low-frequency component image. The method includes downsampling the low-frequency component image to generate a downsampled low-frequency component image. The method includes correcting color aberration of the downs ampled low-frequency component image to generate a color-corrected downsampled low-frequency component image. The method includes upsampling the color-corrected downsampled low-frequency component image to generate a color-corrected low-frequency component image. The method includes combining the color-corrected low-frequency component image and the high-frequency component image to generate a color-corrected version of the image.

Abstract: In one implementation, a method includes obtaining an image. The method includes splitting the image to produce a high-frequency component image and a low-frequency component image. The method includes downsampling the low-frequency component image to generate a downsampled low-frequency component image. The method includes correcting color aberration of the downsampled low-frequency component image to generate a color-corrected downsampled low-frequency component image. The method includes upsampling the color-corrected downsampled low-frequency component image to generate a color-corrected low-frequency component image. The method includes combining the color-corrected low-frequency component image and the high-frequency component image to generate a color-corrected version of the image.

Abstract: In one implementation, a method includes obtaining an image. The method includes correcting color aberration of the image comprising, for a particular pixel of the image by determining one or more chromatic characteristic values for the particular pixel, determining a likelihood that the particular pixel exhibits color aberration based on the one or more chromatic characteristic values for the particular pixel, generating a filtered version of the particular pixel by filtering the particular pixel using pixels in a neighborhood surrounding the particular pixel, and generating a color-corrected version of the particular pixel based on the likelihood that the particular pixel exhibits color aberration and the filtered version of the particular pixel.

Abstract: In various implementations a method includes obtaining a plurality of source images, stabilizing the plurality of source images to generate a plurality of stabilized images, and averaging the plurality of stabilized image to generate a synthetic long exposure image. In various implementations, stabilizing the plurality of source images includes: selecting one of the plurality of source images to serve as a reference frame; and registering others of the plurality of source images to the reference frame by applying a perspective transformation to others of the plurality of the source images.

Abstract: In various implementations, a method includes obtaining a target image having a first resolution and comprising a plurality of target pixels having a plurality of corresponding target pixel values, obtaining a guide image having a second resolution and comprising a plurality of guide pixels having a plurality of corresponding guide pixel values, and generating an enhanced target image based on the target image and the guide image, the enhanced target image having the second resolution and comprising a plurality of enhanced target pixels having a plurality of corresponding enhanced target pixel values. In various implementations, determining, for a particular upscaled target pixel, a similarity metric indicative of the similarity of a neighborhood of pixels around the particular upscaled target pixel to a neighborhood of pixels around a corresponding guide pixel, and determining, for the particular upscaled target pixel, an enhanced target pixel value based on the similarity metric.

Abstract: In various implementations, a method includes obtaining a target image having a first resolution and comprising a plurality of target pixels having a plurality of corresponding target pixel values, obtaining a guide image having a second resolution and comprising a plurality of guide pixels having a plurality of corresponding guide pixel values, and generating an enhanced target image based on the target image and the guide image, the enhanced target image having the second resolution and comprising a plurality of enhanced target pixels having a plurality of corresponding enhanced target pixel values. In various implementations, determining, for a particular upscaled target pixel, a similarity metric indicative of the similarity of a neighborhood of pixels around the particular upscaled target pixel to a neighborhood of pixels around a corresponding guide pixel, and determining, for the particular upscaled target pixel, an enhanced target pixel value based on the similarity metric.

Abstract: In various implementations, a method includes obtaining a target image having a first resolution and comprising a plurality of target pixels having a plurality of corresponding target pixel values, obtaining a guide image having a second resolution and comprising a plurality of guide pixels having a plurality of corresponding guide pixel values, and generating an enhanced target image based on the target image and the guide image, the enhanced target image having the second resolution and comprising a plurality of enhanced target pixels having a plurality of corresponding enhanced target pixel values. In various implementations, determining, for a particular upscaled target pixel, a similarity metric indicative of the similarity of a neighborhood of pixels around the particular upscaled target pixel to a neighborhood of pixels around a corresponding guide pixel, and determining, for the particular upscaled target pixel, an enhanced target pixel value based on the similarity metric.

Abstract: In various implementations, a method includes obtaining a target image having a first resolution and comprising a plurality of target pixels having a plurality of corresponding target pixel values, obtaining a guide image having a second resolution and comprising a plurality of guide pixels having a plurality of corresponding guide pixel values, and generating an enhanced target image based on the target image and the guide image, the enhanced target image having the second resolution and comprising a plurality of enhanced target pixels having a plurality of corresponding enhanced target pixel values. In various implementations, determining, for a particular upscaled target pixel, a similarity metric indicative of the similarity of a neighborhood of pixels around the particular upscaled target pixel to a neighborhood of pixels around a corresponding guide pixel, and determining, for the particular upscaled target pixel, an enhanced target pixel value based on the similarity metric.

Abstract: In various implementations a method includes obtaining a plurality of source images, stabilizing the plurality of source images to generate a plurality of stabilized images, and averaging the plurality of stabilized image to generate a synthetic long exposure image. In various implementations, stabilizing the plurality of source images includes: selecting one of the plurality of source images to serve as a reference frame; and registering others of the plurality of source images to the reference frame by applying a perspective transformation to others of the plurality of the source images.