Sharp has patented an image filtering apparatus with a loop filter including neural network filters and an adaptive loop filter to enhance image quality. The technology involves processing unfiltered images to output a filtered image with improved quality. GlobalData’s report on Sharp gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Sharp, Adaptive video coding was a key innovation area identified from patents. Sharp's grant share as of January 2024 was 29%. Grant share is based on the ratio of number of grants to total number of patents.

Image filtering apparatus with neural network filters and adaptive loop filter

Source: United States Patent and Trademark Office (USPTO). Credit: Sharp Corp

A recently granted patent (Publication Number: US11889070B2) discloses an image filtering apparatus designed to filter input images using neural network filters and an adaptive loop filter. The apparatus includes a first neural network filter that receives the input image and an image of a quantization parameter, outputting a first image. A second neural network filter then processes either the input image or the first output image to produce a second output image. Finally, an adaptive loop filter combines the input image, the first output image, and the second output image to generate a filtered image.

Furthermore, the patent describes an image decoding apparatus that utilizes the image filtering apparatus as a filter for decoded images, as well as an image encoding apparatus that applies the filtering apparatus to input images. The second neural network filter is highlighted as a subset of the first neural network filter, with the ability to output one or multiple intermediate layers of the first neural network filter as the second output image. This innovative approach to image filtering showcases the integration of neural networks and adaptive filters to enhance image processing capabilities.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.