邊緣相似度及其在散斑噪聲抑制算法比較中的應用

邊緣相似度及其在散斑噪聲抑制算法比較中的應用

對于濾波算法,噪聲抑制能力和邊緣保持能力一直是考核其性能的兩個重要指標。對于前者,通常都有相應的參數進行表征,而對于后者,通常卻只能依靠人眼進行主觀評判。根據標準邊緣圖像和待測邊緣圖像邊緣點位置的相似性,定義了邊緣相似度參數,用來表征濾波算法的邊緣保持能力。將此參數應用于高斯噪聲圖像和椒鹽噪聲圖像濾波算法的比較中,取得了預期的效果:此參數值準確地反映了各濾波算法的邊緣保持能力。對激光雷達圖像而言,散斑噪聲濾波算法的邊緣保持能力具有非常重要的意義,為此,將邊緣相似度用于散斑噪聲濾波算法的邊緣保持能力比較,結果表明Lee 濾波算法和增強Lee 濾波算法具有較強的邊緣保持能力,而常規的均值濾波和中值濾波邊緣保持能力較差。

Suppression ability and edge2preserving ability are two important indexes to evaluate a filter algorithm.Proper parameter is used to measure the former , but usually only subjective judgment by human eyes can be used in evaluating the latter one. Edge similar degree parameter was defined to measure the edge2preserving ability of a filter algorithm in the paper based on the similarity between the position of edge point s in standard edge image and the
edge image to be measured. The parameter was used to compare the filter algorithms in processing Gaussian noise affected images and salt & pepper noise affected images. Prospective result was gained and approved that the parameter value measured exactly the edge preserving ability of filter algorithms. The edge2preserving ability of speckle noise filter algorithm is very important to laser radar image. So , the edge similar degree was used to measure the edge2preserving ability of speckle noise filter algorithms. The result showed that Lee filter algorithm and enhanced Lee filter algorithm have preferable edge2preserving ability. The edge2preserving ability of average filter and median filter is dissatisfactory.