摘要
图像分块处理能够有效降低计算过程的复杂程度,减少图像文件所占的空间大小,然而这也导致了块效应的产生,以及由于噪声导致的重构处理后图像的质量损失。为此,提出了改进压缩感知算法的图像处理方法。该方法首先对块效应的出现进行剖析,然后采用压缩感知算法对图像进行分块迭代处理,设计了一种新型权重滤波方法,融合了二次滤波,优化了常规自适应滤波算法。通过仿真对比验证,本文提出的新型图像处理方法能够对图像纹理细节进行有效处理,明显提高了图像的处理质量。
The image processing block can effectively reduce the computational complexity of the process, reducing the size of the space occupied by the image file, but it also leads to the block effect, and the mass loss due to image noise induced after reconstruction？ Therefore, an image processing method based on improved compressed sensing algorithm is proposed？ Firstly, the block effect is analyzed, and then the compressed sensing algorithm is used to segment the image, In this paper, a new weighted filtering method is designed, which is combined with the two filter？ Through simulation and comparison, In this paper, a new image processing method is proposed, which can effectively improve the image quality？
出处
《电子测试》
2017年第6期47-48,共2页
Electronic Test
基金
2017年重庆市教育委员会科学技术项目(基于压缩域DCT参数特征的镜头边缘检测研究)
项目编号:KJ1728400
关键词
压缩感知
图像处理
图像纹理
滤波
Compressed Sensing
Image Processing
Image Texture
filtering
