结合阈值去噪与边缘优化的图像增强算法

针对图像在传输过程中容易出现干扰的问题，该文通过研究图像的增强技术，通 过对比分析，提出了一种结合阈值去噪与边缘优化的图像增强算法，该算法结合小波Contourlet 变换与人眼的视觉固有特性，有效地对分解后的图像系数进行分类，并结合改进边缘优化算法 的增益因子来优化边缘区信号；而非边缘区采用改进后的软阈值去噪算法进行去噪处理。经实 验，该算法具有准确性高与去噪能力强的特性，能够在去噪的同时有效保护边缘信号，与预期 目标相符，具有一定的实用价值。

Image Enhancement Algorithm Combining with Threshold De-noising andEdge Optimization

Image is prone to interference problems in the transmission process. By studying the image enhancement technology and comparative analysis, an image enhancement algorithm is proposed combining with the threshold de-noising and edge optimization. The algorithm is based on the Wavelet Contourlet transform and the inherent characteristics of the human visual. The decomposed image coefficients are classified. The edge area signal is optimized by using the improved edges of the gain factor optimization algorithm. The non-edge of the area is de-noised by improved soft threshold de-noising algorithm. The experiments show the algorithm has the characteristics of high accuracy and de-noising ability, and it can effectively protect edge signal while de-noising. The experimental results are consistent with the expected target.