模糊图像的不连续边缘智能检测改进算法

针对传统不连续边缘检测算法利用增强图像边缘对比度进行检测, 只适用于检测灰度值变化不强烈及含有普通噪声的图像边缘, 检测性能具有局限性的问题, 提出一种模糊图像的不连续边缘智能检测改进算法. 首先通过广义交叉验证准则获取图像噪声方差估计值, 对图像中高斯噪声进行判别, 使用自适应模糊滤波器对含噪图像进行模糊滤波处理; 然后采用改进模糊图像边缘检测算法, 按图像含噪情形制定边缘检测策略, 获取模糊图像边缘； 最后通过灰度形态学的模糊图像不连续边缘检测算法, 对模糊图像边缘受灰度值不均匀变化形成的膨胀、 腐蚀、 形态学梯度型不连续边缘进行检测. 实验结果表明, 该算法抗噪性较高, 模糊图像不连续边缘检测的结果更清晰、 完整.

Improved Algorithm for Intelligent Detection ofDiscontinuous Edges of Blurred Images#br#

Aiming at the problem that the traditional discontinuous edge detection algorithm was used to detect the edge contrast of the enhanced image, but it was only suitable for detecting the edge of the image with no strong change of gray value and ordinary noise, and thedetection performance had the limitation, we proposed an improved algorithm for intelligent detection of discontinuous edges of blurred images. Firstly,the estimation of the noise variance of the image was obtained by the gene ralized cross validation criterion to discriminate the Gauss noise in the image, and the adaptive fuzzy filter was used to make fuzzyfiltering of the noisy image. Secondly, the improved image edge detection algorithm of blurred image was used to acquire the edge of the blurred image byformulating the image edge detection strategy according to the situation of image noise. Finally, the discontinuous edge detection algorithm of blurred image ofgray morphology was used to detect the expansion, corrosion and morphologic gradient discontinuous edges of the blurred image edge caused by the uneven change of gray value. The experimental results show that the proposed algorithm has high noise immunity, and the results of discontinuous edge detection of the blurred image are clearer and more complete.