The Research Of Remote Sensing Image Enhancement Algorithm Based On NSCT And Shearlet Transform

Image is one of the most direct and important source of information for human beings. But it will easily effected by the external factors during the acquisition and transmission of images, often makes the image is not very ideal, and bring inconvenience for subsequent processing. Therefore, the image enhancement is a key link in the image preprocessing stage.There are two traditional methods to enhance the image. Fuzzy algorithm is a method between the two methods, the image pixels are mapped to the fuzzy domain, and process the correlation coefficient as nonlinear method to achieve the purpose of image contrast enhancement. This paper studied the Nonsubsampled Contourlet and the Shearlet transform and combined with fuzzy contrast enhancement algorithm and multi-scale Retinex, the main work is as follows:1、A new threshold algorithm is proposed which is combined with NSCT and improved fuzzy sets. The image is decomposed by the Nonsubsampled Contourlet Transform. Firstly, linear enhancement is used in low frequency sub-band; secondly, the improved adaptive threshold function is used to deal with the high frequency coefficient. Finally, the improved fuzzy contrast is used to enhance the image edge details and the gamma correction is used to enhance the global contrast. Experimental results show that the proposed algorithm can significantly improve the image visual effect, and enhance image details.2、An image enhancement algorithm based on Shearlet transform was proposed. The image was decomposed into low frequency components and high frequency components by Shearlet. Firstly, multi-scale Retinex was used to enhance the low frequency components of Shearlet decomposition to remove the effect of illumination on image; secondly, threshold function was used at high frequency coefficients of each scale and direction to suppress noise. Finally, fuzzy contrast enhancement method was used to the reconstruction image to improve the overall contrast of image. Experiment results show that proposed algorithm is effective in improving the conditions of illumination and enriching the texture details on the remote sensing images.