论文部分内容阅读
本文提出一种对比度增强-噪声滤波处理方法,用于改善微光图象的视觉性能.通过修改图象的局部亮度均值和对残差分量加权来提高图象的局部对比度.文中将Kalman滤波技术用于图象的降噪处理,基于图象的实际相关性质,我们推导了一种近似算法,这种近似在不降低估计精度的前提下,使算法的计算量和存贮量大大下降.该方法不要求关于原图的任何先验知识,所需参数均从降质图象中估计.实验证明利用该方法处理微光图象,可获得比较满意的效果.
In this paper, a contrast-enhanced-noise filtering method is proposed to improve the visual performance of the glimmer image, and the local contrast of the image is improved by modifying the local mean value of the image and weighting the residual component.In this paper, Kalman filtering For the image denoising processing, based on the actual correlation properties of the image, we derive an approximation algorithm that greatly reduces the amount of computation and storage of the algorithm without reducing the estimation accuracy. The method does not require any prior knowledge about the original image, and the required parameters are estimated from the degraded image. Experiments show that the proposed method can be used to deal with the low-light image with satisfactory results.