Medical image have the characteristics of the complex overlapping of organ and tissue, and accompanied by noise, local volume effect, artifact. So the traditional segmentation method is not ideal. To solve this problem, a medical image segmentation algorithm based on tree-structured MRF in wavelet domain (WTS-MRF) was proposed. For expressing medical image information. WTS-MRF model defines the same tree structure at every scale of wavelet decomposition. At the same time, wavelet transform has good directional selectivity, non-redundancy and multi-scale characteristics. Multiscale and multi direction expression by wavelet decomposition improved the ability of TS-MRF to describe the non-stationary characteristics of images. Then, it can more accurately describe the statistical characteristics of images, and effectively extract the feature information of medical image. In the WTS-MRF model, there are two structures in the layer TS-MRF structure and the interlayer four fork tree structure of wavelet coefficient. The TS-MRF model is built in the layer, and the node potential function is modeled by Potts model. The Gaussian model is used to build the model for the observed characteristics with the same label. The interlayer wavelet coefficients have the property of first-order Markov. The maximum posterior probability is obtained by recursive operation, and the classification hierarchy tree label is implemented to realize medical image segmentation. the experiment results indicate that the algorithm not only can effectively extract the details but also can relatively completely extract target area of medical image, and has higher segmentation accuracy and robustness.
According to traditional methods of image segmentation on sonar image processing with less robustness and the problem of low accuracy, we propose the method of sonar image segmentation based on Tree-Structured Markov Random Field(TS-MRF), the algorithm shows better ability in using spatial information. First, using a tree structure constraint two-valued MRF sequences to model sonar image, through the node to describe local information of image, hierarchy information establish interconnected relationships through nodes, at the same time when we describe the hierarchical structure information of the image, we can preserve an image’s local information effectively. Then, we define split gain coefficients to reflect the ratio that marking posterior probability division before and after the splitting on the assumption of the known image viewing features, and viewing gain coefficients of judgment as the basis for determining binary tree of node split to reduce the complexity of solving a posterior probability. Finally, during the process of image segmentation, continuing to split the leaf nodes with the maximum splitting gain, so we can get the splitting results. We add merge during the process of segmentation. Using the methods of region splitting and merging to reduce the error division, so we can obtain the final segmentation results. Experimental results show that this approach has high segmentation accuracy and robustness.
KEYWORDS: Digital watermarking, Wavelets, Image compression, Visualization, Linear filtering, Digital imaging, Discrete wavelet transforms, Digital filtering, Image processing, Image filtering
As a new technique used to protect the copyright of digital productions, the digital watermark technique has drawn extensive attention. A digital watermarking algorithm based on discrete wavelet transform (DWT) was presented according to human visual properties in the paper. Then some attack analyses were given. Experimental results show that the watermarking scheme proposed in this paper is invisible and robust to cropping, and also has good robustness to cut , compression , filtering , and noise adding .
According to the characteristic of noise in the laser exploration system, threshold circuit is often utilized in traditional
method, but the thresholds which are adopted in this kind of algorithm are not adaptive. When the circuit is confirmed,
the threshold is also confirmed, so the algorithm can not adapt the requirement of detecting weak signal in high noise.
This paper analyses how to choose the threshold of denoising based on noise features in laser exploration system, and
also analyses alterable MRA threshold method in details. The algorithm which is adopted in this paper solve the problem
of how to filter the noise whilst to keep the details of the signal. The result shows that the new algorithm has better
effect.
KEYWORDS: Web services, Logic, Evolutionary algorithms, Composites, Silicon, Artificial intelligence, Chemical species, System on a chip, Electronics engineering, Distributed computing
For automatic service composition, a planning based framework MOCIS is proposed. Planning is based on two major
techniques, service reasoning and constraint satisfaction. Constraint satisfaction can be divided into quality constraint
satisfaction and quantity constraint satisfaction. Contrary to traditional methods realizing upon techniques by interleaving
activity, message and provider, the novelty of the framework is dividing these concerns into three layers, with activity
layer majoring service reasoning, message layer for quality constraint and provider layer for quantity constraint. The
layered architecture makes automatic web service composition possible for activity tree that abstract BPEL list and
concrete BPEL list are achieved automatically with each layer, and users can selection proper abstract BPEL or BPEL to
satisfy their request. And E-traveling composition cases have been tested, demonstrating that complex service can be
achieved through three layers compositing automatically.
KEYWORDS: Edge detection, Wavelets, Image processing, Image filtering, Detection and tracking algorithms, Medical imaging, Digital filtering, Data processing, Detector arrays, Medicine
Image edge is because the gradation is the result of not continuously, is image's information basic characteristic, is also
one of hot topics in image processing. This paper analyzes traditional arithmetic of image edge detection and existing
problem, uses adaptive lifting wavelet analysis, adaptive adjusts the predict filter and the update filter according to
information's partial characteristic, thus realizes the processing information accurate match; at the same time, improves
the wavelet edge detection operator, realizes one kind to be suitable for the adaptive lifting scheme image edge
detection's algorithm, and applies this method in the medicine image edge detection. The experiment results show that
this paper's algorithm is better than the traditional algorithm effect.
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