Wavelet based nonlinear image enhancement for Gaussian and uniform noise

Wenzhe Li, Ji-Nan Lin, R. Unbehauen
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引用次数: 3

Abstract

We consider image enhancement by using a wavelet based nonlinear filtering scheme. It is well-known that the wavelet transform decomposes an image into a finite number of resolution scales that is very suitable for image analysis and image compression. Such a resolution decomposition is also useful for noisy image enhancement, in view of that the visible noise can be suitably separated in the low-frequency (LF) component and the high-frequency (HF) components of a wavelet transform. While the wavelet transform is used for the decomposition and reconstruction of images, we apply nonlinear piecewise-quadratic (PWQ) filters for the processing of the decomposed progressive wavelet HF components before reconstruction. We show by simulations that such a filtering scheme can achieve a considerable improvement in noise smoothing, details-preserving and the visual quality of images.
基于小波的高斯和均匀噪声非线性图像增强
我们考虑使用基于小波的非线性滤波方案来增强图像。众所周知,小波变换将图像分解为有限个分辨率尺度,非常适合于图像分析和图像压缩。由于小波变换的低频(LF)分量和高频(HF)分量可以适当地分离可见噪声,因此这种分辨率分解对噪声图像增强也很有用。在小波变换用于图像分解和重建的同时,我们采用非线性分段二次(PWQ)滤波器对分解后的渐进式小波高频分量进行处理,然后再进行重建。仿真结果表明,该滤波方案在噪声平滑、细节保留和图像视觉质量等方面均有显著改善。
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