Semi-Huber potential function for image segmentation
نویسندگان
چکیده
منابع مشابه
Image Segmentation Using Semi-Supervised k-Means
Extracting the region of interest is a very challenging task in Image Processing. Image segmentation is an important technique for image processing which aims at partitioning the image into different homogeneous regions or clusters. Lots of general-purpose techniques and algorithms have been developed and widely applied in various application areas. In this paper, a Semi-Supervised k-means segm...
متن کاملAn Improved Pixon-Based Approach for Image Segmentation
An improved pixon-based method is proposed in this paper for image segmentation. In thisapproach, a wavelet thresholding technique is initially applied on the image to reduce noise and toslightly smooth the image. This technique causes an image not to be oversegmented when the pixonbasedmethod is used. Indeed, the wavelet thresholding, as a pre-processing step, eliminates theunnecessary details...
متن کاملAn improved image graph for semi-automatic segmentation
The problem of semi-automatic segmentation has attracted much interest over the last few years. The Random Walker algorithm [1] has proven to be quite a popular solution to this problem, as it is able to deal with several components, and models the image using a convenient graph structure. We propose two improvements to the image graph used by the Random Walker method. First, we propose a new w...
متن کاملSemi-supervised Learning of Edge Filters for Volumetric Image Segmentation
For every segmentation task, prior knowledge about the object that shall be segmented has to be incorporated. This is typically performed either automatically by using labeled data to train the used algorithm, or by manual adaptation of the algorithm to the specific application. For the segmentation of 3D data, the generation of training sets is very tedious and time consuming, since in most ca...
متن کاملSemi-supervised statistical region refinement for color image segmentation
Some authors have recently devised adaptations of spectral grouping algorithms to integrate prior knowledge, as constrained eigenvalues problems. In this paper, we improve and adapt a recent statistical region merging approach to this task, as a nonparametric mixture model estimation problem. The approach appears to be attractive both for its theoretical benefits and its experimental results, a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Optics Express
سال: 2012
ISSN: 1094-4087
DOI: 10.1364/oe.20.006542