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机构地区:[1]上海交通大学自动化系图像处理与模式识别研究所,上海200240
出 处:《计算机应用与软件》2009年第11期234-238,258,共6页Computer Applications and Software
摘 要:提出一种新的基于Retinex理论的图像增强算法。这个新算法将双边滤波作为一个去噪环节加入传统的Retinex算法,在实验中有效地抑制了传统Retinex算法中没有解决的噪声问题,从而大大改善了图像增强的处理效果。具体来说,双边滤波器实现简单,并且它的非迭代性和保边性能够在迅速有效去噪的同时保持图像的边界不被模糊减弱。一般被用来去噪的平滑滤波器都容易使物体的边界模糊,与它们相比,用双边滤波器进行去噪不仅较好地平衡了平滑去噪与避免过度模糊的关系,也在处理时间和处理效果上找到了平衡点。同时,实验证实传统Retinex处理后放大的噪声主要来自原图的较暗区域,这使得我们可以在仅处理较暗区域的情况下得到满意的结果。另一方面,通过传统Retinex对原图中光照成分的估计,也使较暗区域能够比较方便地被识别出来。只对较暗区域进行局部处理的做法不仅可以避免在噪声较低的区域造成过度平滑,也能够节省大量的处理时间从而提高处理速度。In this paper,a new Retinex theory-based image enhancement method is proposed. In the new method, bilateral filter is combined to the classical Retinex algorithm as a denoising phase, in experiments this modification greatly suppressed the noise which the classical Retinex model didn' t overcome and thus improved processing results of image enhancement conspicuously. In particular, bilateral filter is simple to realise,moreover,its non-iterative and edge-preserving properties can suppress noise quickly while preserve image edges from blurred weakening. In contrast with other smoothing filters used for suppressing noises that all of them tend to blur the object boundaries, the bilateral filter performs best in balancing the smoothly denoising and over-blurring as well as trades-off between the time consumption and the processing results. Furthermore, experiments prove that the noise amplified by classical Retinex treatment mainly comes from the dark regions in input image,which guarantees that satisfactory results could he produced by only denoising the darker regions. Fortunately, the darker regions could be identified easily with the illumination component decomposition executed on input image by classical Retinex. Such regional processing only in darker parts could avoid over-smoothing in regions with lower noise, and could further accelerate the processing speed on account of cutting off a great deal of processing time.
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