Image display method and image processing method
An image display and image processing technology, applied in the field of image processing, can solve the problems of complex and changeable use occasions, and achieve the effects of increasing image perception depth, improving human perception contrast, and increasing depth of field
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no. 1 example
[0035] The first embodiment of the present invention performs image segmentation processing on the original image to find the large-scale edge in the original image, and then increases the edge step at the large-scale edge to obtain a relatively sharp edge contour, and then obtains the target image with increased global contrast , the specific steps are, for example:
[0036] First, the original image is obtained and image segmentation is performed on the obtained original image to obtain large-scale edges in the original image.
[0037] There are many ways to obtain large-scale edges. For example, the K-means clustering algorithm is used to segment the original image, K=2, that is to say, the original image is divided into two pieces to obtain the foreground and background areas of the original image. Get the large-scale edges of the original image.
[0038] Then, the original image is edge-sharpened by countershading method to obtain sharp edge steps at the large-scale edge...
no. 2 example
[0046] The difference between the second embodiment and the aforementioned first embodiment lies in: the implementation method of increasing (or sharpening) the edge brightness step at the large-scale edge, which uses the unsharpening mask (UnsharpeningMask) method to enhance the large-scale image Strength of brightness steps at scale edges. Specifically, it can be:
[0047] First, blur the luminance channel of the original image to obtain a blurred image, that is, segment the base layer containing large-scale edges in the luminance channel (or luminance component) of the original image. Specifically, a 5*5 Gaussian filter (which is An edge-preserving image filter) performs low-pass filtering on the original image, filters out the high-frequency part in the brightness channel of the original image, and obtains a base layer containing large-scale edges corresponding to the low-frequency part of the original image, thereby realizing image Segmentation is processed and large-sca...
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