Advanced Materials Research Vols. 433-440

Abstract: This paper use the technology to process satellite image, combined with sampling and analysis, to establish the mathematical relationship model between the algal primary productivity of Ebinur Lake with the spectral information of satellite imagery, inversion of algae plant primary productivity, then get the conclusion: Based on satellite image processing technology to study the algae plant primary productivity, measured during the growth of algae plant in the total primary productivity of 99.5 t; CBERS-2 was been found that is fit for measure the primary productivity of algae plant Ebinur Lake, the characteristic of the Green band is the accuracy band; the optimal inversion model is B = 3.945-0.033G-0.005 (GR) +0.128 (G / B).

Abstract: Face is the greatest superior biometric as the face has a complex, multidimensional and meaningful identity compared from one person to another. Face identification is executed by comparing the characteristics of the face (test image) with those of known individual images in the database. This paper describes the used of the Principal Component Analysis (PCA) algorithm for human face identification based on webcam image. The MATLAB is used as a tool for image processing and analysis. The important decision to identify the person is by the minimum distance of the face images and known face images in face space. From the results, it can be concluded that the work has successfully implemented the PCA algorithm for human face identification through a webcam.

Abstract: Remote sensing image information extraction research is one of the key problems of remote sensing research, it is also one of the hot and difficult points in remote sensing research., In this paper,NDVI images for the study of synthesis of haloxylon ammdendron forest 16 days of MODIS is taken as research object, aimed at improving the precision of information extraction, focuses on the NDVI time effects on phenology of haloxylon ammdendron woodland response, tell woodland diagnosis point of information, using diagnostic points of haloxylon forest information analysis and extraction of results and field visits, mutatis mutandis, the results showed information extraction accuracy has improved.

Abstract: As the issuing and implementation of “the outline about curriculum reform of elementary education (trial rule, 2001)”, 18 sets of Course Standards and newly edited textbooks with all types and all courses are experimented on the trial plots for Chinese Basic Education. What normal universities should do to response the curriculum reform with the heaviest efforts and widest area since the establishment of the nation Normal universities is responsible for professional training, the unique characteristics of aesthetics curriculum resources take natural advantage of promoting the development of new courses. The thesis analyzes the curriculum resource status in Arts department, puts up simply the tactics on the development and use of curriculum resources on campus and off campus, and hope that crude remarks may draw forth by abler people.

Abstract: This paper concerns the problem of image mosaic. An image matching method based on SIFT features and an image blending method of improved Hat function are proposed in the paper. SIFT feature is local feature and keeps invariant to scale zoom, rotation and illumination. It is also insensitive to noise, view point changing and so on. Because of this our method is insensitive to orientation, scale and illumination of input images, so it’s possible to accomplish image mosaic between arbitrary matching images and the Hat function blending algorithm with global intensity revise makes the mosaic image accepted by human eyes.

Abstract: In this paper, we present a novel method for segmentation of cerebral blood vessels form magnetic resonance angiography(MRA) images using optimal flow based on Bayesian selecting scheme algorithm. First the multi-distribution regression algorithm is applied to MIP to decrease the quantity of mixing elements. Then the probability-control selecting scheme is put forward to divide the local neighbor into brain vessels and other tissues with consistent motion vector. Finally, the optimal flow algorithm is adopted to refine the vector and get the final result. The feasibility and validity of the algorithm is verified by the experiment. With the algorithm, small branches of the brain vessels can be segmented, and the accuracy of segmentation is improved. Experimental results on head MRA dataset confirm the efficiency of the proposed approach.

Abstract: The research presented in this paper aims at improving the accuracy of land-use maps produced from classification of Landsat images of mega cities in developing countries. In other words, the main objective of this paper is to find a suitable post classification technique that gives optimum results for Landsat images of mega cities in developing countries. To reach our goal, the paper presents a classification of two TM-Landsat sub scenes using a traditional statistical classifier (Maximum Likelihood) into four land cover classes (vegetation-water-Desert-Urban); then the accuracy assessment for the produced land-cover map will be calculated. Following to this step, three post processing techniques- Majority Filter, Probability label Relaxation (PLR), and Cellular Automata (CA) - will be applied in order to improve the accuracy of the previously produced land cover map. Finally, the same accuracy assessment measurements will be calculated for the two land-cover maps produced by each of the above post classification techniques. Initial results will show that CA outperformed the other techniques. In this paper we propose a methodology to implement a satellite image post classification Algorithm with cellular Automata.

Abstract: The pseudo-color processing for target identification and tracking is very meaningful Experimental results show that the pseudo-color image fusion is a very effective methods. This paper presents a false color image fusion based on the new method. Fusion using wavelet transform grayscale images, find the gray fused image and the difference between the original image, respectively, as the image of l, α, β components are color fusion image, and then after the color transformation, the final false color fused image. The results showed that the color fusion image colors more vivid, more in line with human visual characteristics.

Abstract: The white balance is an important parameter of digital camera which makes a great impact on the application of digital cameras. However, due to the limitations of hardware of digital camera, the output image of digital camera cannot restore true colors of the objects under the different light sources conditions. And existing automatic white balance (AWB) algorithms have many application restrictions, particularly the single color image, the algorithms always failure to adjust. To solve this problem, this paper proposes an optimized algorithm based on the gray world assumption and HSI color model. According to the R, G and B color components probability distribution, the algorithm adjusts the image by using the difference value of color. Experimental results show that our algorithm can adjust images in complex situations; meanwhile these confirm that this method is not only effective, but also has the advantage of easy realization.

Abstract: An efficient compressed volume rendering algorithm is presented. Firstly, the original volume data is compressed by a content-based classified hierarchical vector quantization algorithm. Secondly, the compressed volume data is then transferred to Graphic Processing Unit and decompressed in real time, subsequently, the decompressed data is rendered by a three-dimensional textures mapping method to accelerate the speed of rendering. Experimental results show that, in addition to reasonable fidelity and faster rendering speed, the presented algorithm can obtain multiple levels of detail on the off-the-shelf graphic hardware.