In the paper, an auto-adaptive refinement algorithm based on wavelet transform for electrical impedance imaging has been presented. The scale of mesh division affects the computation cost and the quality of reconstructed image. In order to trade off the two aspects, adaptive mesh refinement is applied to increase the efficiency of reconstruction algorithm by reducing computation and storage cost as well as providing problem-dependent solution structures. The resultant mesh model and reconstructed impedance distribution are shown in comparison with that of uniform mesh refinement.
In this paper the method is presented to retrieve based on image content in video database using DC-image. The DC-image with the DC coefficient is extracted from DCT domain of image in this video database model. The principle of DC-image and three different extraction methods of the DC-image from MPEG video stream are described. With the DC-image, temporary segmentation of compress video is realized depending the histogram of DC-image. Comparing the performance of three extracting methods and analyzing the result of DC-image extracted by different methods, we propose a video database structure and feature extraction method. To create the uniform indexing for video clip, the expression format of frame is developed by normalized histogram of DC-image.
An effective approach to increase the image resolution in static electrical impedance tomography is proposed, in which the image with local high resolution is reconstructed by fine meshing only the impedance abnormal element in the finite element model based on a genetic algorithm. Experimental results from a laboratory phantom are presented.
The fractional Fourier transform is the powerful tool for time-variant signal analysis. For space-variant degradation and non-stationary processes the filtering in fractional Fourier domains permits reduction of the error compared with ordinary Fourier domain filtering. In this paper the concept of filtering in fractional Fourier domains is applied to the problem of estimating degraded images. Efficient digital implementation using discrete Hermite eigenvectors can provide similar results to match the continuous outputs. Expressions for the 2D optimal filter function in fractional domains will be given for transform domains characterized by the two rotation angle parameters of the 2D fractional Fourier transform. The proposed method is used to restore images that have several degradations in the experiments. The results show that the method presented in this paper is valid.
A system for the electrical impedance tomography is described in the paper. A digital signal processing (DSP) chip is used to control the operation of every module. As DSP is easy for high-speed control and flexible for embed algorithm and data preprocessing, the system can sample the data and reconstruct the impedance variation distribution quickly that makes the real time image monitoring possible. At here, the principle, implementation and performance of the system are illustrated. And the experimental result, the reconstructed impedance variation distribution image, shows the efficiency of the system.
A new method used to improve the quality of the electrical impedance dynamic imaging is presented in the paper. It uses local refinement to change the finite element discretization while the refined areas are selected by the man and machine interaction. As a result, the accuracy and resolution of the reconstructed image are increased but the computation amount and the stability of the algorithm are maintained. Experiment validates the efficiency of the method.
Image segmentation is one of the most important operations in many image analysis problems, which is the process that subdivides an image into its constituents and extracts those parts of interest. In this paper, we present a new second order difference gray-scale image segmentation algorithm based on cellular neural networks. A 3x3 CNN cloning template is applied, which can make smooth processing and has a good ability to deal with the conflict between the capability of noise resistance and the edge detection of complex shapes. We use second order difference operator to calculate the coefficients of the control template, which are not constant but rather depend on the input gray-scale values. It is similar to Contour Extraction CNN in construction, but there are some different in algorithm. The result of experiment shows that the second order difference CNN has a good capability in edge detection. It is better than Contour Extraction CNN in detail detection and more effective than the Laplacian of Gauss (LOG) algorithm.
A system for the electrical impedance tomography is described in the paper. A digital signal processing (DSP) chip is used to control the operation of every module. As DSP is easy for high-speed control and flexible for embed algorithm and data preprocessing, the system can sample the data and reconstruct the impedance variation distribution quickly that makes the real time image monitoring possible. At here, the principle, implementation and performance of the system are illustrated. And the experimental result, the reconstructed impedance variation distribution image, shows the efficiency of the system.
Video communication aiming at public switched telephone network (PSTN) applied with voice-band modem is attractive because of its low-cost facilities and the wide coverage of PSTN around the world, The key technique of video transmission over PSTN with voice-band modem is very low bit-rate video coding. Video coding based on discrete wavelet transform has become a hot research topic. But while in very low bit-rate video coding applications, the peak signal to noise ratio (PSNR) and the visual quality of image reconstructions are not very satisfactory by using the general orthogonal or biorthogonal wavelet which does not match well with human visual system characteristics. In this paper, a new kind of compact biorthogonal wavelet based on the modulation transfer function for human visual system model is used in very low bit-rate video coding scheme, in which a new improved Goh's 3D wavelet transform and motion compression technique are applied. The experimental results indicate that the new coding scheme using the constructed compact biorthogonal wavelet has a good performance in average PSNR, compression ratios and visual quality of image reconstruction when compared to the other motion-compensated 2D and 3D coding schemes based on the general biorthogonal wavelet transform.
As an important analysis tool, wavelet transform has made a great development in image compression coding, since Daubechies constructed a kind of compact support orthogonal wavelet and Mallat presented a fast pyramid algorithm for wavelet decomposition and reconstruction. In order to raise the compression ratio and improve the visual quality of reconstruction, it becomes very important to find a wavelet basis that fits the human visual system (HVS). Marr wavelet, as it is known, is a kind of wavelet, so it is not suitable for implementation of image compression coding. In this paper, a new method is provided to construct a kind of compactly supported biorthogonal wavelet based on human visual system, we employ the genetic algorithm to construct compactly supported biorthogonal wavelet that can approximate the modulation transform function for HVS. The novel constructed wavelet is applied to image compression coding in our experiments. The experimental results indicate that the visual quality of reconstruction with the new kind of wavelet is equivalent to other compactly biorthogonal wavelets in the condition of the same bit rate. It has good performance of reconstruction, especially used in texture image compression coding.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)