De-interlacing method with the motive detection and self-adaptation weight filtering

Abstract

The disclosed removing interlace method using motion detection and adaptive weighting filter comprises: filtering the last field, current field and follow-up field of the image signal; storing in SDRAM as pre-set format; based on pixel waiting for interpolation in current field, calculating the motion level of last and follow-up field pixel, then calculating the motion information weighting value for mixing; mixing two interpolation by motion information weighting, and outputting the mixed value. This invention can hold image space feature and vertical details without precise motion information estimation, reduces design complexity, and improves design reliability.

Description

technical field [0001] The invention belongs to the field of video processing of digital television integrated circuits, and in particular relates to a de-interlacing method using motion detection and self-adaptive weighted filtering. Background technique [0002] Due to the limitation of the technical level, the early TV adopts interlaced scanning method based on the compromise of video transmission bandwidth and image quality, so that the total amount of information of each picture is reduced to half of the original, and the visual persistence effect of the human eye makes viewing The obtained two images are blurred into one frame image, thus obtaining a relatively smooth visual effect. However, with the gradual practical use of large-screen TVs and high-definition TVs, interline flicker, interfield flicker and crawling phenomena caused by interlaced scanning are becoming more and more obvious, resulting in a decline in image quality. In order to suppress and eliminate th...

AI Technical Summary

Problems solved by technology

In order to overcome the aforementioned deficiencies of the prior art, the object of the present invention is to provide a de-interlacing device and method using motion detection and adaptive weighted filtering, to make up for and eliminate the shortcomings of the motion adaptive algorithm being greatly affected by noise and inaccurate motion detection, As well as the disadvantage of high complexity in hardware implementation of the motion compensation algorithm, it can not only maintain the spatial characteristics of the image but also maintain the vertical details of the image. At the same time, it does not require accurate motion information estimation, which can improve the de-interlacing effect and greatly reduce the complexity of hardware design. , improve design reliability, easy hardware implementation

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