123 results about "Temporal noise" patented technology

A content-dependent scan rate converter with adaptive noise reduction that provides a highly integrated, implementation efficient de-interlacer. By identifying and using redundant information from the image (motion values and edge directions), this scan rate converter is able to perform the tasks of film-mode detection, motion-adaptive scan rate conversion, and content-dependent video noise reduction. Adaptive video noise reduction is incorporated in the process where temporal noise reduction is performed on the still parts of the image, thus preserving high detail spatial information, and data-adaptive spatial noise reduction is performed on the moving parts of the image. A low-pass filter is used in flat fields to smooth out Gaussian noise and a direction-dependent median filter is used in the presence of impulsive noise or an edge. Therefore, the selected spatial filter is optimized for the particular pixel that is being processed to maintain crisp edges.

An apparatus for removing a noise of a video signal is disclosed, by which a noise level can be effectively estimated to enhance an image quality of the video signal, by which the noise can be removed in a manner of effectively estimating a noise level though motion adaptive filtering, and by which blurring is prevented in the process of removing the noises. The present invention includes a temporal noise level estimation unit estimating a level of a temporal noise included in the video signal using a difference between two temporally consecutive videos, a noise correction unit correcting a noise estimated by the temporal noise level estimation unit, and a noise removal unit removing the noise included in the video signal using a level of the corrected noise.

A method and apparatus are provided for eliminating image noise to remove spatial-temporal noise and improve visibility. The method includes extracting a spatial-temporal noise level of neighbor pixels around a current pixel, filtering noise of the current pixel by applying a weight to spatial-temporal pixels around the current pixel based on the extracted spatial-temporal noise level, and applying a weight to the noise-filtered pixel and a boosted-up pixel based on an edge intensity and summing the weight-applied pixels. The spatial-temporal noise level is extracted based on spatial-temporal information of neighbor pixels around a current pixel in a current frame and spatial-temporal information of neighbor pixels around a current pixel in a previous frame.

A method of reducing noise in a sequence of digital video frames is performed by motion estimation between a current noisy frame and a previous noise-reduced frame, to generate motion vectors indicating relative motion between the pixels in the current noisy frame and the corresponding pixels in the previous noise-reduced frame; and removing noise from the current noisy frame by computing the weighted average of pixels in the current noise frame and the corresponding pixels in the previous noise-reduced frame based on the motion vectors, to generate a noise-reduced output frame.

Noise is reduced in a video system by applying motion compensated temporal filtering using previously generated motion vectors and adaptive spatial filtering at scene change frames. Various types of noise can be introduced into video prior to compression and transmission. Artifacts arise from recording and signal manipulation, terrestrial or orbital communications, or during decoding. Noise introduced prior to image compression interferes with performance and subsequently impairs system performance. While filtering generally reduces noise in a video image, it can also reduce edge definition leading to loss of focus. Filtering can also tax system throughput, since increased computational complexity often results from filtering schemes. Furthermore, the movement of objects within frames, as defined by groups of pixels, complicates the noise reduction process by adding additional complexity. In addition to improvements made to FIR spatial filtering, the present invention improves on previous filtering techniques by using Infinite Impulse Response (IIR) temporal filtering to reduce noise while maintaining edge definition. It also uses motion vectors previously calculated as part of the first-pass image encoding or alternatively by trans coding to reduce computational complexity for P-frame and B-frame image preprocessing. Single stage P-frame temporal noise filtering and double stage B-frame temporal noise filtering are presented.