Research On Interpolation To Enlarge The Image And Multi-threshold Region Growing Algorithm

Segmentation in the field of image analysis is a fundamental question. Generally, the problem of image segmentation is defined as an image or data set is separated into a series of the same results. Although image segmentation algorithm has been great improvement and breakthrough, but in practical application, there is still a great difficulty. The traditional methods of regional growth have significant limitations. This paper sought to innovate in methods. Solution will be divided into three categories:the former division, the division handling, processing after the split. And put forward an algorithm of multi-threshold region growing. It can effectively reduce the segmentation regions. The algorithm can be expressed as:in the process of immersion, through the re-definition of the threshold function, making a number of pixels can be immersed in an earlier, the partition of the region has significantly reduced, thereby the results of segmentation are more accurate.The main work and innovation are as follows:1. Introduce commonly used algorithm and application of the methods. Based on this, we introduce the evaluation method of image segmentation.2. Dealing with the pretreatment clarity about image, we have done some preparatory work of the necessary improvement about image clarity. In this paper, it introduces an algorithm of improving the histogram equalization. We get the image after processing with this algorithm, it will not only improve the clarity of image, but give a good visual effect. They can also make preparations for the latter partition.3. The size of pretreatment image is related to the speed of image segmentation, so we need the image zoom in and out. It introduces a new image-reduction approach:it processes the image zoom in and out using the combination of morphology and interpolation method, the effect is significant. Not only to maintain a clear edge of the fairing, but also ensure the image clarity after shrinking.4. Against a lot of limitations of the traditional region growing algorithm, the paper introduces the concept of regional growth based on the repeated definition of the threshold function, it can ensure the right direction and regions of region growing of the image.