Grating-type substrates with nanometer dimensions offer the possibility of enhancing the electromagnetic field close to surface. Binary silver grating has been used to investigate the Surface-enhanced Raman Scattering (SERS). This paper describes the electromagnetic theory of SERS effect on the surface of a binary silver grating with nanometer dimension and discusses the TM-polarized incident light because surface plasmons excitation require this polarization . Laplacian's equation is given for this model in the grating region. We use the rigorous coupled wave analysis (RCWA) to solve the Maxwell differential equations in the grating region . The consideration of optimum incident angles for different gratings is also shown by analyzing the surface plasmon (SP) excitation . SERS enhancement factor is considered for binary grating with respect to the influence of angle incidence, grating depth and ratio of grating ridge width to grating period on both surface plasmon and SERS enhancement factor. Compared with the other SERS surface models, such as the isolated spheres model and other irregular models, this one-dimension regular model allows more quantitative estimates of the surface structures for the SERS effect.
Proc. SPIE. 5637, Electronic Imaging and Multimedia Technology IV
KEYWORDS: Information fusion, Image processing algorithms and systems, Wavelet transforms, Tissues, Magnetic resonance imaging, Image segmentation, Image processing, Medical imaging, 3D image processing, Brain
A novel method providing a supervised processing of medical image for segmentation is presented. This method was based on a pyramid-structured wavelet-transform and improved watershed transform algorithm. The method contains three consecutive stages: image segmentation based on multi-resolution watershed transform, region projection and mergence with extracted multi-future information, edge refinement based on fuzzy information fusion. In the processing, both texture and gray variation information are used inside the tissue regions, and only gradation information is used near the edges of regions. Experimental results for the proposed algorithm indicate feasibility and reliability for certain medical images segmentation.
With rapid development of electronic imaging and multimedia technology, the telemedicine is applied to modern medical servings in the hospital. Digital medical image is characterized by high resolution, high precision and vast data. The optimized compression algorithm can alleviate restriction in the transmission speed and data storage. This paper describes the characteristics of human vision system based on the physiology structure, and analyses the characteristics of medical image in the telemedicine, then it brings forward an optimized compression algorithm based on wavelet zerotree. After the image is smoothed, it is decomposed with the haar filters. Then the wavelet coefficients are quantified adaptively. Therefore, we can maximize efficiency of compression and achieve better subjective visual image. This algorithm can be applied to image transmission in the telemedicine. In the end, we examined the feasibility of this algorithm with an image transmission experiment in the network.
A design of spectrometer is presented, which uses a holographic grating and a two-dimensional color CCD camera connected with PC via video format port. And in the image post-procession, a real-time frame calculus technique and a non-linear filter were applied to provider higher image quality and better resistant to background noise. With improved designed zoom mechanics, the device has a wide resolution dynamic range and high frequency, since it can gather more spectrum information than linear black-white CCD. The spectrum analysis experiments for water quality detection indicate that the device can meet variant requirements of analysis at low cost.