Image division method based on watershed-quantum evolution clustering algorithm
A watershed algorithm and quantum evolution technology, applied in the field of image processing, can solve the problems of inaccurate edge positioning, regional consistency performance affecting image segmentation, and time-consuming, achieving good segmentation effect, efficient parallelism, and reduced time complexity. Effect
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[0032] refer to figure 1 , the segmentation process of the present invention is as follows:
[0033] Process 1, the image to be segmented is divided into blocks.
[0034] 1.1) Input the image to be segmented, and simplify the image to be segmented;
[0035] The purpose of simplification is to remove small noise interference and details that are not important to perception, and smooth the image. Here, one of the most commonly used tools in morphology is selected to open the morphological reconstruction filter. Compared with classical image reduction tools, such as low-pass or medium-pass filters, the advantage of morphological reconstruction filters is to simplify the image without blurring the image or changing the image contour.
[0036] 1.2) Calculate the morphological gradient image of the simplified image;
[0037] The morphological gradient image reflects the change of the gray level in the image, and has a larger gradient value at the edge where the gray value change...
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