短弧氙灯光谱特性及其在太阳模拟器中应用

短弧氙灯作为标准光源得到了广泛的应用,但是空间光谱分布的不均匀性限制了其进一步的发展。通过对短弧氙灯轴向光谱分布的测量,电弧温度分布的计算,初步得到温度与电流密度的关系,认为可以通过控制弧电流密度改善氙灯光谱辐照度分布。

基于光纤光谱仪的LED光学特性测试

以海洋光学实验仪器(光谱仪、积分球、光纤、电源)为测量系统,搭建发光二极管(LED)光源特性测试平台,通过Spectra Suite软件对LED的光学特性数据获取与处理,分别测试白光、红光、黄绿光、蓝绿光、黄光和蓝光LED的光学性质。用光谱仪USB2000+与USB650 Red Tide获得各种LED光的辐射通量光谱分布图、发光强度光谱分布图、色品图,以及各单色光LED半宽度、峰值波长、色坐标、主波长、色纯度等数据,并对不同颜色的LED进行光学性能对比。实验结果表明,蓝光LED波峰辐射通量最大,红光LED单色性最好,红光的色纯度最大。简要比较光谱仪USB2000+与USB650 Red Tide在测量结果上的区别。

Window shrink contourlet coefficients for image denoising

An adaptive image denosing technique was proposed to achieve the tradeoff between details retain and noises removal. In order to achieve this objective, the contourlet transform was introduced and a new threshold method, namely CWinShrink, is presented. It shrinks the contourlet coefficients with adaptive shrinkage factors. The shrinkage factors were calculated with reference to the sum of squares of the contourlet coefficients within the neighborhood window. This approach achieves enhanced results for images those are corrupted with additive Gaussian noise. In numerical comparisons with various methods, for a set of noisy images （the PSNR range fi＇om 10.86dB to 26.91dB） , the presented method outperforms VisuShrink and Wiener filter in terms of the PSNR. Experiments also show that this method not only keeps the details of image but also yields denoised images with better visual quality.

Sub-pixel mapping method based on BP neural network

A new sub-pixel mapping method based on BP neural network is proposed in order to determine the spatial distribution of class components in each mixed pixel.The network was used to train a model that describes the relationship between spatial distribution of target components in mixed pixel and its neighboring information.Then the sub-pixel scaled target could be predicted by the trained model.In order to improve the performance of BP network,BP learning algorithm with momentum was employed.The experiments were conducted both on synthetic images and on hyperspectral imagery(HSI).The results prove that this method is capable of estimating land covers fairly accurately and has a great superiority over some other sub-pixel mapping methods in terms of computational complexity.

The nature of[S Ⅲ]λλ9096,9532 emitters at z=1.34 and 1.23

A study of[S Ⅲ]λλ9096,9532 emitters at z=1.34 and 1.23 is presented using our deep narrow-band H2S 1(centered at 2.13μm)imaging survey of the Extended Chandra Deep Field South(ECDFS).We combine our data with multi-wavelength data of ECDFS to build up spectral energy distributions(SEDs)from the U to the Ks-band for emitter candidates selected with strong excess in H2S 1 Ks and derive photometric redshifts,line luminosities,stellar masses and extinction.A sample of 14[S Ⅲ]emitters are identified with H2S 1<22.8 and Ks<24.8(AB)over 381 arcmin2area,having[S Ⅲ]line luminosity L[S Ⅲ]=~1041.5 42.6erg s 1.None of the[S Ⅲ]emitters is found to have X-ray counterpart in the deepest Chandra 4 Ms observation,suggesting that they are unlikely powered by AGNs.The HST/ACS F606W and HST/WFC3 F160W images show their rest-frame UV and optical morphologies.About half of the[S Ⅲ]emitters are mergers and at least one third are disk-type galaxies.Nearly all[S Ⅲ]emitters exhibit a prominent Balmer break in their SEDs,indicating the presence of a significant post-starburst component.Taken together,our results imply that both shock heating in post-starburst and photoionization caused by young massive stars are likely to excite strong[S Ⅲ]emission lines.We conclude that the[S Ⅲ]emitters in our sample are dominated by star-forming galaxies(SFGs)with stellar mass 8.7<log(M/M⊙)<9.9.