Method and device for obtaining boundary strength and removing block effect

Abstract

The embodiment of the invention discloses a method of obtaining plate boundary filtering strength; the method comprises: ensuring the similar threshold value, utilizing the similar threshold value to calculate the area flatness; ensuring the filtering strength initial value of the plate boundary according to the area flatness interval of the area flatness; each area flatness interval corresponding to a filtering strength initial value; utilizing the head information of the block at two sides of the obtained plate boundary, adjusting the filtering strength initial value, obtaining the plate boundary filtering strength, or utilizing the head information of the block comprising type information or coding mode information, judging whether needs to filter the pixel of the block at two sides of the plate boundary; the embodiment of the invention further discloses a device for obtaining plate boundary filtering strength; the embodiment of the invention further discloses a method and device of removing the block effect; utilizing the invention is able to improve the accuracy of obtaining the plate boundary filtering strength.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method and a device for obtaining block boundary strength and removing block effect. Background technique [0002] In video coding standards such as H.264 and digital audio and video codec technology standards, images need to be processed in blocks. For example, the basic processing unit of the H.264 standard is 16×16 macroblocks. After each block is transformed and quantized, block effects will appear to varying degrees, that is, discontinuous visual mutations will appear on the block boundaries between blocks. The blocking effect is caused by the quantization error caused by the block processing during quantization. According to the different image content in the block range, there are mainly two different manifestations, one is trapezoidal noise, and the other is lattice noise. The above two kinds of noise will make the edges of the image obvious or even blocky areas. Speci...

AI Technical Summary

Problems solved by technology

[0092] From the above analysis of the current method of removing block effect, it can be seen that when obtaining BS to determine the filtering process, the similarity threshold can be obtained after two table lookups, and the root does not make full use of the relationship between blocks on both sides of the block boundary. and header information, so the BS obtained by judging is inaccurate, which makes the current method of removing block effect unable to use effective filtering process to remove block effect, so the performance of removing block effect is poor

[0093] To sum up, the current method of obtaining block boundary filtering strength, the obtained BS is inaccurate, which makes the current method of removing block effect unable to effectively reduce block effect

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