基于独立分量分析的图像增强

提出了一种基于独立分量分析的图像增强算法，传统的独立分量分析要求观测信号的个数不能小于源信号的个数，无法直接对单个图像进行去噪处理，为了能够利用独立分量分析分离图像中的加性噪声，需要构造一个观测图像，认为图像中的噪声和图像数据的信息是相互统计独立的，由含噪图像估计出噪声图像作为独立分量分析的另一个观测图像，进行独立分量分析，从而实现图像与噪声的分离。计算机仿真结果表明，利用本算法可较好地保留原图像的信息，获得较好的消噪效果，提高了图像的信噪比。

Image Enhancement Algorithm Based on Independent Component Analysis

An image enhancement algorithm base on independent component analysis is proposed. The standard independent component analysis algorithm require that the number of sensors is more than or equal to that of sources, so it is impossible to apply independent component analysis to image enhancement directly. In this paper, a algorithm for constructing a noise image is proposed for noise reduction based on ICA, thereby noise and original image can be separated through ICA. Simulation result shows that much better denoise effect and signal-noise ration can be obtained by using this algorithm.