Abstract: Embodiments relate to an image processing circuit that performs machine learning (ML) based noise reduction on image data. The image processing circuit includes a ML based noise reduction circuit that includes a hybrid kernel calculation circuit and a noise filtering circuit coupled to the hybrid kernel calculation circuit. The hybrid kernel calculation circuit generates, for each pixel of an image, a hybrid kernel by combining a ML kernel of each pixel of the image and a bilateral kernel of each pixel of the image. The noise filtering circuit performs, for each pixel of the image, noise filtering of the image using the hybrid kernel for each pixel of the image to generate a de-noised version of the image.

Abstract: An electronic image capture device captures a first image of a scene at a first time. A first local tone mapping operator for a first portion of the first image is determined. The electronic image capture device further captures a second image of the scene at a second time. A motion of the electronic device between the first time and the second time is determined. A second local tone mapping operator for a second portion of the second image is determined. The second portion is determined to correspond to the first portion based, at least in part, on the determined motion of the electronic device. The second local tone mapping operator is determined based, at least in part, on the first local tone mapping operator. At least the second local tone mapping operator is applied to the second portion of the second image.