Abstract: A method for processing a video with a dynamic video-based super-resolution network and a circuit system are provided. In the method, quality scores used to assess a quality of an input video are calculated based on image features of the input video. A moving average algorithm is performed on the quality scores of multiple frames of the input video for obtaining a moving average score. Two corresponding weight tables are selected according to the moving average score. The two weight tables are used to calculate a blending weight that is applied to a neural network super-resolution algorithm. The blending weight is applied to the neural network super-resolution algorithm, so as to produce an output video.

Abstract: The present disclosure discloses an image enlarging apparatus having deep learning mechanism. A deep learning circuit includes an image downsizing circuit, an image characteristic analyzing circuit, a weighting reallocating circuit and an image upsizing circuit. The image downsizing circuit downsizes an input image to generate a downsized image. The image characteristic analyzing circuit analyzes the downsized image according to image characteristics to generate categorized images. The weighting reallocating circuit performs weighting reallocating on the categorized images according to image weighting parameters corresponding to the image characteristics to generate weighting reallocated images. The image upsizing circuit upsizes the weighting reallocated images to generate adjusted images. A concatenating circuit concatenates the input image and the adjusted images to generate concatenated images.

Abstract: An image processing system includes: a first image processing device for performing a first image enhancement process on a source image to generate a first enhanced image; one or more second images processing device, each of which is used to perform a second image enhancement processing on a size-reduced image generated based on the source image, and accordingly to output one or more second enhanced images whose size identical to the source image; and an output controller for analyzing regional frequency characteristics of the source image to generate an analysis result, determining one or more region weights according to the analysis result, and synthesize the first enhanced image with the one or more second enhanced images according to the one or more region weights, thereby to generate an output image.

Abstract: An image processing system includes: a material image generating circuit, at least one texture generating circuit and an output controller. The material image generating circuit is configured to generate a material image. The at least one texture generating circuit is coupled to the material image generating circuit, and configured to adjust texture characteristics of the material image to generate at least one texture image. The output controller is coupled to the at least one texture generating circuit, and configured to analyze regional characteristics of a source image to generate an analysis result, determine a region weight according to the analysis result, and synthesize the source image with the at least one texture image according to the region weight, thereby to generate an output image.