压缩传感图像边缘自适应增强方法研究

Research on Edge Adaptive Enhancement Method of Compressed Sensing Image

传感图像存储过程中受压缩处理的影响,造成边缘细节模糊,为此,提出基于加性小波的压缩传感图像边缘自适应增强方法。基于高斯平滑滤波算法对压缩传感图像进行去噪处理,对经过去噪处理的图像展开多尺度加性小波分形,采用形态学梯度对低频图像进行滤波处理,获取形态学梯度图。通过模极大值方法提取边缘,叠加多层边缘信息获取高频边缘图。将形态学梯度图和高频边缘图两者作加性小波逆变换,对逆变换结果进行二值化处理,获取压缩传感图像边缘图,实现边缘自适应增强。主观测试结果表明,所提方法可以准确增强压缩后传感图像的边缘;客观测试结果表明,所提方法信息熵均值为7.81、平均梯度为7.89、对比度为273.7,可以获取较多的图像边缘细节。

The edge details of the compressed sensing image are blurred due to the influence of compression processing in the storage process of the sensing image.Therefore,an adaptive edge enhancement method based on additive wavelet is proposed for the compressed sensing image.The compressed sensor image is denoised based on the Gaussian smoothing filtering algorithm.The denoised image is processed by adopting multi-scale additive wavelet fractal,and the low-frequency image is filtered by adopting morphological gradient to obtain the morphological gradient image.The edge is extracted by using modulus maximum method,and the high-frequency edge image is obtained by superimposing multi-layer edge information.The morphological gradient image and high-frequency edge image are transformed through the inverse additive wavelet transform,and the results of the inverse transform are binarized to obtain the edge image of the compressed sensing image to achieve adaptive edge enhancement.Subjective test results show that the proposed method can accurately enhance the edge of the compressed sensing image.The objective test results show that the average information entropy of the proposed method is 7.81,the average gradient is 7.89,and the contrast is 273.7.Therefore,more image edge details can be obtained.