Abstract: A method and processing system for applying upsampling to input pixel values of frames of a sequence of frames to determine upsampled pixel values at upsampled pixel locations. A jitter pattern is used over the sequence such that different frames of the sequence have input pixel values at locations corresponding to different upsampled pixel locations. An initial block of upsampled pixel values is determined for a current frame. An aligned block of upsampled pixel values for the current frame is determined based on the initial block in accordance with the jitter pattern. A block of refinement values for the initial block of upsampled pixel values is determined for the current frame, and is applied to the initial block to determine a refined block of upsampled pixel values.

Abstract: An image of a 3-D scene is rendered by rendering a noisy image at a first resolution; obtaining initial guide channels at the first resolution, and obtaining corresponding initial guide channels at a second resolution. When the two resolutions are the same, the initial guide channels at the first resolution and the corresponding initial guide channels at the second resolution may be provided by a single set of initial guide channels. Enhanced guide channels are derived from the initial guide channels using machine learning models. For each of a plurality of local neighbourhoods, the parameters of a denoising model that approximates the noisy image (in the local neighbourhood) are calculated as a function of the enhanced guide channels (at the first resolution), and the calculated parameters are applied to the one or more enhanced guide channels (at the second resolution), to produce a denoised image at the second resolution.

Abstract: An image of a 3-D scene is rendered by rendering a noisy image at a first resolution; obtaining initial guide channels at the first resolution, and obtaining corresponding initial guide channels at a second resolution. When the two resolutions are the same, the initial guide channels at the first resolution and the corresponding initial guide channels at the second resolution may be provided by a single set of initial guide channels. Enhanced guide channels are derived from the initial guide channels and the noisy image, using machine learning models. For each of a plurality of local neighbourhoods, the parameters of a denoising model that approximates the noisy image as a function of the one or more enhanced guide channels (at the first resolution) are calculated, and the calculated parameters are applied to the one or more enhanced guide channels (at the second resolution), to produce a denoised image at the second resolution.

Abstract: A method and a processing module are provided for applying upsampling to input pixels representing an image region to determine a block of upsampled pixels. The input pixels have locations corresponding to a repeating quincunx arrangement of upsampled pixel locations. The input pixels are analysed to determine one or more weighting parameters, the one or more weighting parameters being indicative of a directionality of filtering to be applied when upsampling is applied to the input pixels within the image region. One or more of the upsampled pixels of the block of upsampled pixels are determined in accordance with the directionality of filtering indicated by the determined one or more weighting parameters.

Abstract: Pixel values are determined at respective upsampled pixel locations for a current frame of a sequence of frames. Depth values are obtained for locations of pixels of a reference frame of the sequence of frames. For each of the upsampled pixel locations: (a) a depth value of the current frame is obtained; (b) a motion vector is obtained to indicate motion between the reference frame and the current frame; (c) the motion vector is used to identify one or more of the pixels of the reference frame; (d) a weight is determined for each of the identified pixels of the reference frame in dependence on: (i) the depth value of the current frame for the upsampled pixel location, and (ii) the depth value for the location of the identified pixel of the reference frame; and (e) the pixel value for the upsampled pixel location is determined using the determined weight for each of the identified pixels.

Abstract: An indication of one or more weighting parameters is determined for use in applying upsampling to input pixel values representing an image region to determine a block of one or more upsampled pixel values. A horizontal edge filter determines a first filtered value. A vertical edge filter determines a second filtered value. A horizontal line filter determines a third filtered value. A vertical line filter determines a fourth filtered value. The first, second, third and fourth filtered values are used to determine the indication of one or more weighting parameters, wherein the one or more weighting parameters are indicative of relative horizontal and vertical variation of the input pixel values within the image region. The determined indication of the one or more weighting parameters is output for use in applying upsampling to the input pixel values representing the image region to determine a block of one or more upsampled pixel values.

Abstract: A method of optimising an image signal processor (ISP), which is to be used to process sensor image data generating output image data. The method may include obtaining sensor image data; processing the sensor image data according to one or more ISP settings to produce output image data; producing quality metric data associated with the output image data and optimising the one or more ISP settings based on the quality metric data.

Abstract: A method of optimising an image signal processor (ISP), which is to be used to process sensor image data generating output image data. The method may include obtaining sensor image data; processing the sensor image data according to one or more ISP settings to produce output image data; producing quality metric data associated with the output image data and optimising the one or more ISP settings based on the quality metric data.