Abstract: Various image sharpening techniques are disclosed. For example, a method for image sharpening includes obtaining, using at least one sensor of an electronic device, an image that includes visual content. The method also includes generating an edge map that indicates edges of the visual content within the image. The method further includes applying a high-pass signal and an adaptive gain based on the edge map to sharpen the image. The method also includes generating a bright halo mask and a dark halo mask based on the edge map, where the bright halo mask indicates an upper sharpening limit and the dark halo mask indicates a lower sharpening limit. In addition, the method includes modifying a level of sharpening at one or more of the edges within the sharpened image to provide halo artifact reduction based on the bright halo mask and the dark halo mask.

Abstract: An electronic device includes at least one imaging sensor and at least one processor coupled to the at least one imaging sensor. The at least one imaging sensor is configured to capture a burst of image frames. The at least one processor is configured to generate a low-resolution image from the burst of image frames. The at least one processor is also configured to estimate a blur kernel based on the burst of image frames. The at least one processor is further configured to perform deconvolution on the low-resolution image using the blur kernel to generate a deconvolved image. In addition, the at least one processor is configured to generate a high-resolution image using super resolution (SR) on the deconvolved image.

Abstract: Various image sharpening techniques are disclosed. For example, a method for image sharpening includes obtaining, using at least one sensor of an electronic device, an image that includes visual content. The method also includes generating an edge map that indicates edges of the visual content within the image. The method further includes applying a high-pass signal and an adaptive gain based on the edge map to sharpen the image. The method also includes generating a bright halo mask and a dark halo mask based on the edge map, where the bright halo mask indicates an upper sharpening limit and the dark halo mask indicates a lower sharpening limit. In addition, the method includes modifying a level of sharpening at one or more of the edges within the sharpened image to provide halo artifact reduction based on the bright halo mask and the dark halo mask.

Abstract: An electronic device includes at least one imaging sensor and at least one processor coupled to the at least one imaging sensor. The at least one imaging sensor is configured to capture a burst of image frames. The at least one processor is configured to generate a low-resolution image from the burst of image frames. The at least one processor is also configured to estimate a blur kernel based on the burst of image frames. The at least one processor is further configured to perform deconvolution on the low-resolution image using the blur kernel to generate a deconvolved image. In addition, the at least one processor is configured to generate a high-resolution image using super resolution (SR) on the deconvolved image.