Image Segmentation Algorithm Based On Wavelet Transform And Watershed Algorithm

Image segmentation is one of the most important issues in the image processing; it is also the fundamental of low-level computer vision. Image segmentation is to represent an image as a set of connected regions. It is the foundation of image understanding and analysis. The segmented quality of image has directly impact on the image processing steps.The accuracy real-time image and speed of segmentation processing system are import for real-time image processing. Watershed segmentation based on mathematical morphology is a popular tool for image and parallelizable. It processing. It is easy, intuitive, rapidly computational can get a connected and closed profile. But there is much "over segmentation" in the segmentation results. To improve the accuracy of segmentation result and the speediness of segmentation algorithm, we fulfill the following work:1)First,the author made a detailed study of the mathematical description and realization method of watershed transform, as well as the the causes of "over-segmentation" phenomenon.2) Through access to information, the author has understood the application of wavelet transform in image processing, especially in image enhancement and image detection.3) After making Comparison of watershed algorithm and wavelet transform applications in image processing, the author proposes a reasonable algorithm design.4) The author made application of the new-designed image segmentation method, and compared it with the related images.5) Results analysis.