Digital image automatic speckle-removing method
A digital image and speckle technology, which is applied in image enhancement, image data processing, instruments, etc., can solve the problems of inconvenient and fast, and many steps of freckle removal.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2013-12-11
Smart Images
Figure 1 Figure 2 Figure 3
Abstract
Description
technical field
[0001] The invention relates to a digital image processing method, in particular to an image processing method for automatically removing spots in the digital image. Background technique
[0002] With the popularization of digital portable devices, a large number of digital camera devices are also used in various devices including mobile phones and tablet computers, which greatly reduces the threshold for users to take photos, and various life-related shooting can be completed through simple operations. , which is very convenient. In particular, taking selfies of individuals has become a common behavior in our daily life, and has even been used as a technical means of socializing. This type of shooting for portraits, especially for facial makeup, usually requires adjustment and beautification of the image after taking a selfie. One of the more common operations of this type is to remove some unwanted elements in the image (such as acne, spots, moles, etc.)....
Examples
Embodiment Construction
[0068] A kind of method of digital image automatic spot removal in the present embodiment, it comprises the following steps:
[0069] 1) Receive a face image A digital image A, carry out grayscale processing to image A, obtain grayscale image B; This processing adopts one of following two formulas:
[0070] Gray=0.299*Red+0.587*Green+0.114*Blue:
[0071] Gray=(Red*306+Green*601+Blue*117+512) / 1024;
[0072] Wherein, Gray is the gray value of each pixel of the grayscale image B, and Red, Green, and Blue are the color values of the red, green, and blue channels of each pixel of the image A respectively;
[0073] 2) Perform contrast enhancement processing on the grayscale image B, the formula is:
[0074] nResult=nColor+(nColor-128)*(1.0+Contrast) / 255
[0075] Among them, nResult represents the gray value after contrast enhancement, nColor represents the gray value to be contrast enhanced, and Contrast represents the intensity of contrast enhancement, which is 0.15;
[0076]...