Image processing implementation method and system

Abstract

The invention discloses an image processing implementation method and system, and the method comprises the steps: obtaining a to-be-filtered original image which is H in height and W in width; whereinR is the radius corresponding to the mean value, the expansion operation core and the corrosion operation core, the window size of the corresponding core is 2R + 1, and R is greater than 0; performing upper and lower boundary extension processing on the original image according to the radius R; performing left and right boundary extension processing on the image after the upper and lower boundaryextension processing; and outputting the target image according to a preset performance function. According to the image algorithm provided by the invention, except that the column direction and theradius R are related to edge extension and first calculation, the rest mean filtering and expansion corrosion operations are irrelevant to the radius; according to the method, the required memory amount is small, the algorithm flow storage data is less, mean filtering, expansion and corrosion operations are realized by adopting a unified framework, and the performance and the application value ofthe graphic image algorithm are greatly improved.

Description

technical field [0001] The present invention relates to the field of image technology, in particular, to an image processing implementation method and system. Background technique [0002] The three basic image algorithms, mean filtering, binary image expansion operation and erosion operation, are widely used in the field of graphics and images, and many complex algorithms also include one or more of these three basic algorithms. For example, the basic structure of GuidedFilter consists of multiple mean filters; algorithms such as opening and closing of binary images require basic expansion and erosion operations. [0003] At present, the complexity of many of the above three basic algorithms is often related to the size of the computing core (2R+1). When the computing core increases the computing complexity, the required memory space also increases rapidly, and there is no unified algorithm structure. Therefore, an image algorithm that has nothing to do with the size of t...

AI Technical Summary

Problems solved by technology

[0003] At present, the complexity of many of the above three basic algorithms is often related to the size of the computing core (2R+1). When the computing core increases the computing complexity, the required memory space also increases rapidly, and there is no unified algorithm structure

Images