An Image Processing Method Based on Rotational Jitter Matrix Processing

Abstract

The invention relates to an image processing method based on rotation dither matrix processing. In order to solve the problem that the accuracy of the existing rotation dither matrix processing method is not high enough, the present invention proposes a technical solution of inter-frame error accumulation. By combining the inter-frame error accumulation with the rotation dither matrix processing method, lower bit bandwidth can be achieved. express the purpose of the original image more completely. In addition, when the present invention also uses a 2×2 rotation dither matrix, it uses less resource overhead than the existing rotation dither matrix processing method. At the same time, it can express the original data information more completely, which greatly saves resources.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image processing method based on rotation and dithering matrix processing. Background technique [0002] With the development of science and technology, it has entered the state of information explosion, especially video image data, because of its intuitiveness of conveying and expressing information, its application range is getting wider and wider, and the ensuing problem is how to use less resource overhead Save more complete video image information. This problem is mainly manifested in two aspects: ① For most of the current 8-bit image data, how to save complete video image information with a small resource overhead such as 5 bits; ② At present, image data with high bit information content, such as 10bit For image data, how to use existing 8bit resources to save relatively complete video image information. [0003] Digital Halftoning Technology (Digital Halftoni...

AI Technical Summary

Problems solved by technology

[0022] However, there are some deficiencies in the existing technology, that is, when using the existing rotation dithering matrix, such as a 2×2 rotation dithering matrix, the original data information can be represented with a data bandwidth of 2 bits less than the original one, but if the original data information is expressed with less than the original When the original data information is represented by 3 bits or less, the accuracy is reduced and some information is lost

For example, a 2×2 rotation dithering matrix is ​​also used. If the data bandwidth of 5bit (32 levels) is used to represent the original 8bit (256 levels) data, for example, 37 of 8bits, then Value=32×37 / 256=4.625=Int +Dec, when processing the decimal part of the pixel value Dec with a 2×2 rotation and dithering matrix, among the four adjacent image frames, the integer part of the pixel value of the corresponding pixel position of three image frames is increased by 1, and the other image frame The integer part of the pixel value corresponding to the pixel position is not added with 1, then the final representation result is 0.75, but the actual fractional part is 0.625, which means the result is not accurate

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