多聚焦图像灰度重叠特征自适应识别仿真

传统方法对多聚焦图像进行预处理,由于图像灰度重叠区域合并使原图像细节信息损失,导致多聚焦图像灰度重叠区域识别效果不理想,为此提出基于Mean-shift算法和OTSU阈值分割算法的多聚焦图像灰度重叠特征自适应识别方法。使用Mean-shift算法对多聚焦图像进行平滑处理,对平滑处理过后的多聚焦图像进行小波变换,将图像的灰度重叠区域灰度值增强;再使用阈值分割将经过灰度增强的重叠区域分类;通过OTSU算法识别出灰度重叠特征区域。实验结果表明,提出方法在图像灰度重叠区域的识别效果上较为突出,并且能够有效保留灰度重叠区域的细节信息。

Multi-Focus Image Gray-Scale Overlapping Feature Adaptive Recognition Simulation

An adaptive recognition method for gray overlapping feature in multi-focus image based on Mean-shift algorithm and OTSU threshold segmentation algorithm was proposed.First of all,the Mean-shift algorithm was used to smooth the multi-focus image,and the multi-focus image after smoothing was transformed by wavelet,so as to enhance the gray value of overlapping region.And then,the overlapping regions after grayscale enhancement were classified by threshold segmentation.Finally,the gray overlapping region was recognized by OTSU algorithm.Simulation results prove that the proposed method is more prominent in recognizing the gray overlapping regions.Meanwhile,this method can effectively preserve the details of gray overlapping regions.