Image sharpening method and mobile terminal

Abstract

The invention discloses an image sharpening method, which includes: a mobile terminal obtains an original RGB image and converts the original RGB image into a YCbCr space image; obtains each pixel intensity information of the brightness component in the YCbCr space image, and The intensity information of each pixel determines the black edge and white edge and their corresponding sharpening intensity; according to the corresponding sharpening intensity of the black edge and white edge, the black edge and white edge are sharpened respectively; the sharpened YCbCr The spatial image is converted into a new RGB image to obtain a sharpened image. The invention also discloses a mobile terminal for image sharpening. The present invention realizes separate sharpening of black edges and white edges to a corresponding degree, thereby improving the sharpening effect of images.

Description

technical field [0001] The invention relates to the technical field of mobile terminals, in particular to an image sharpening method and a mobile terminal. Background technique [0002] In an existing mobile terminal, a series of algorithm processing is generally performed when an image is formed, and finally an ideal image can be output. However, due to a series of image processing, the image will inevitably be blurred and the definition will be reduced, which will seriously affect the visual quality. Therefore, it is necessary to carry out further edge sharpening processing on the image and enhance the edge to improve the visual quality of the image. [0003] In existing image sharpening schemes, for example, based on an unsharp mask algorithm, the black and white edges are sharpened to the same intensity, which will cause serious black and white edges to appear on the edge of the image. However, if the sharpening intensity is reduced, the sharpening intensity of the bla...

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Problems solved by technology

[0003] In the existing image sharpening scheme, for example, based on the unsharp mask algorithm, the black and white edges are sharpened to the same intensity, which will cause serious black and white edges to appear on the edge of the image

However, if the sharpening intensity is reduced, the sharpening intensity of the black part and the white part will be reduced at the same time, so that although the black and white edges are weakened, the image sharpness is also reduced accordingly, making the image effect after sharpening very unsatisfactory. it is good

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