Applied Mechanics and Materials Vols. 687-691

Abstract: Based on the analysis of the characteristic of digital imaging and form, that digital image visual performance of rewriting the traditional visual aesthetic paradigm. The design and the integration of affective communication ability are for the creation of the two-dimensional plane advertisement design provides a new performance space. It has a positive guiding significance. Based on this, this article from is the perspective of plane advertisement design. Summed up the following practical digital imaging visual penetration performance patterns: direct application of deconstruction refactoring, heterogeneous combination, total quality replacement, space-time displacement, deformation and exaggeration and anthropomorphic and combined with the actual application case is analyzed to illustrate arguments. Finally, from the Angle of the audience to digital imaging and visual penetration cognition has carried on the investigation and analysis, combining with related data statistics to verify the digital imaging performance in plane advertisement design, the application of space is very big and worth further research. We are looking forward to digital imaging brings in the two-dimensional plane visual feast for us.

Abstract: For the mutual effects of camera shake and subject movement, the image generation space varying motion blur. In order to achieve image restoration, firstly dividing the image area using the Gaussian background modeling, and updated model adaptive to improve the speed and convergence accuracy. Then use the total variation (TV) of the L1 model to estimate the regional point spread function (PSF), and adopted the edge density weight to reduce small edge’s interference for the PSF estimates. Eventually to restored image by Wiener filter. Through experimental analysis, compared with other algorithms, our algorithms get better results in the space varies motion-blurred image.

Abstract: Aiming at the difficulties in the segmentation for high-resolution remote multispectral sensing images, this paper proposed a segmentation approach for remote sensing images based on texture features. The algorithm implemented precipitation watershed transform respectively on the texture images obtained by the different characteristics of GLCM, and then superimposed the two segmentation results, finally completing the image segmentation by using a novel regional consolidation method that combined the texture features. The experiments were implemented on the high-resolution ALOS and SPOT 5 remote sensing images respectively. Compared with the traditional watershed segmentation approach based on gradient information, the experimental results showed that the proposed algorithm can accurately locate the edges of objects, effectively overcome the phenomenon of over-segmentation and under-segmentation, with a higher segmentation accuracy and stability.

Abstract: This study attempts to introduce parallel computing into processing of remote sensing images and discuss its influence on the processing results. We select an processing of remote sensing images called feature point extraction to run in parallel computing environment and calculate the time consumption and root-mean-square error, then give an analysis based on the result.

Abstract: The flame recognition system based on video image is applied to the fire flame detection, and it can be very good to avoid the shortage of the traditional fire flame detection system. Three frame difference algorithm is adopted to extract the motion features of the flame. And Lab color space is applied in analyzing the flame color. By analyzing the circular degree of the flame and the interference sources, the change rate of the flame area and the angle feature of the fire flame, it can be determined whether there is a fire in the image. The experimental results shows: this algorithm can not only effectively improve the accuracy and real-time performance of the flame detection and identification, but also eliminate the interference of other substances and reduce the misjudgment.

Abstract: Due to the artifact of classical image reconstruction algorithms in texture regions, this paper proposes an adaptive region demosaicking using Multi-Gradients. It first recovers green components according to the operators and the texture regions. Then the chrominance channels are reconstructed based on the interpolated green components and constant-hue rule. Experiments prove that this algorithm can improve the effectiveness from the subjective and objective.

Abstract: Fingerprints are widely used in biometric techniques for automatic personal identification. In this paper, a fingerprint segmentation method is proposed to overcome the bad impact imposed by the complex background of the fingerprint image. The proposed approach is based on combining global and local processing to achieve segmentation of fingerprint images. The approach is implemented in three stages: preprocessing, segmentation, and post-processing. The effectiveness of the proposed method can be confirmed through the experimental results.

Abstract: In image processing, the texture image segmentation is one of the most important issues. Considering the problem that the traditional segmentation methods often fail to the low quality texture image segmentation, this paper proposes a modified OTSU thresholding segmentation method. Experimental results show that the proposed method not only is well adapt to the change of brightness and contrast, but also can be applied to much complex background.

Abstract: This thesis focuses on some key technologies in WMN, including the QoS routing based on the mufti-rate, the cross-layer channel allocation based on the mufti-rate, the cross-layer channel allocation based on the cognitive technique and the Mesh access point selection based on the study. Along the achievements in main line of joint design cooperation, in which carries out in-depth ideas, there form a number of innovative the related technologies.

Abstract: The optical imaging system has the limitation in scope, which is difficult to make all the objects in the same scene clear. To this issue, a multi-scale geometric analysis method – the second-generation Curvelet transform is applied into the fusion of multi-focus image. After the adjustment of the coefficients which are received by the Curvelet transform of more multi-focus image, the result image is gained by the inverse Curvelet transform. Experiments show that this method can have better fusion effect and significantly increase the space quality of multi-focus image.