光学 精密工程, 2014, 22 (11): 3091, 网络出版: 2014-12-08
光学合成孔径复原图像的振铃探测与消除
Detection and removal of ringing artifact for optical synthetic aperture restoration image
图像复原 振铃效应 光学合成孔径 视觉感知 图像分区 双边滤波 image restoration ringing artifact optical synthetic aperture visual perception image classification bilateral filter
摘要
针对相位平移误差使光学合成孔径图像的复原出现的振铃效应, 提出了一种结合视觉感知的振铃探测与消除方法。首先, 提出并利用梯度方向随机度和局部方差值两项指标计算得到图像纹理区;然后, 根据不同阈值的Canny算子检测出全边缘与主边缘, 并将主边缘邻域内的全边缘作为待筛选的边缘振铃;最后, 结合人类视觉系统的纹理掩盖效应分别得到振铃区与平坦区。此外, 在图像分区基础上, 选择亮度相似度因子作为自适应参数, 利用双边滤波进行图像处理。实验显示: 处理后Lena图像的峰值信噪比提高了10.8%, 分辨率板的结构相似度提高了0.057。结果表明: 该方法能够对图像以像素精度分区, 可以在保持边缘与纹理的同时, 有效消除振铃效应, 提高图像复原质量。
Abstract
As phase shift errors will lead to severe ringing artifacts in the restoration results of optical synthetic aperture images, a method to detect and remove the ringing artifacts was proposed based on visual perception. Firstly, the texture region was obtained by calculating the scales of gradient direction randomness and local variance distribution. Then, the whole edges and main edges were separately detected by the Canny operator with different thresholds and whole edges belong to the neighborhood of all edges were considered as the edge ringing candidate. Finally, the ringing region and flat region were respectively derived by combining the texture masking of human visual system. Based on the image classification, the adaptive bilateral filter was applied to removal of the ringing artifacts. Experimental results show that the Peak Signal to Noise Ratio ( PSNR) of a Lena image after processing is improved by 10.8% while the Structural Similarity(SSIM) of resolution board image is improved by 0.057 as well. It condudes that the proposed method classifies the image on pixel scale, so it eliminates the ringing artifacts dramatically while preserving the edges and textures effectively. It is capable of improving the image restoration quality.
魏小峰, 耿则勋, 宋向. 光学合成孔径复原图像的振铃探测与消除[J]. 光学 精密工程, 2014, 22(11): 3091. WEI Xiao-feng, GENG Ze-xun, SONG Xiang. Detection and removal of ringing artifact for optical synthetic aperture restoration image[J]. Optics and Precision Engineering, 2014, 22(11): 3091.