| Since come into being, BioChip has gained widespread regard for its value of clinical practice and research potential, and is the current research focus. BioChip image is a very important part of Biochip technology. How to analyse and process the noised low-contrast BioChip image obtaining from BioChip detector effectively, such as image denoised and low-contrast image enhancement, has become the focus of recent studies with the development of Biochip technology. Aiming at the research status at home and abroad about image analysis and processing at present, some studies are carried out in this paper, and its results are applied to BioChip image availably.Wavelet analysis is often used in nonstationary signal analysis and processing for its good frequency domain analytical characteristic and multiresolution analytical ability, but it is not the optimalizing expression used in image signal with abundant textural features. For excellent line-singularity and anisotropy, Curvelet is the new resreach area of image analysis and processing.Aiming at BioChip image deniose, a new method is put forward in this paper. Based on the second Curvelet transform, and connected Cycle Spinning algorithm, the traditional soft-threshold function is improved through fuzzy function. Experiment results demonstrate that the proposed method has better effect in denoising, and protecting the characteristic of edge details effectively.Aiming at BioChip image Ehancement, an improved nolinear function is given in this paper, and it improve the degree of self-adaptability and avoid the complication of modulating different parameters of nonlinear gain function on general image enhancement arithmetic based on Curvelet transform. In this paper, spatial nonlinear transform and Curvelet nonlinear transform are combined to highlight the whole information, enhance the contrast and perfect visual effects. Experiment results demonstrate that the proposed method has better effect on image enhancement. |
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