一种DWT与背景重构相结合的运动目标分割方法

针对视频处理中数据量大、消耗时间长的缺点,在假定"背景像素总是以较高的频率在图像序列中出现"的前提下,提出了一种新的运动目标分割方法。首先将待处理的视频图像序列经过DWT变换(Discrete Wavelet Trans-form)提取其近似分量,然后利用像素点聚类方法,结合双阈值和相似类合并,选择一段时间内频率出现较高的像素值来重构背景,最后借鉴图像匹配的评价标准来验证重构背景的准确性。实验结果表明,该方法能提取出较好的背景,从而实现对运动目标的高效且完整分割。

Moving Objects Segmentation Method Combining DM and Background Reconstruction

Due to the disadvantage of timcconsuming and large volumes data of video processing, based on the hypothesis that the background pixel intensity always appears in image sequence with maximum probability, a novel method of moving objects segmentation was presented. This approach extracts the approximate components of video images sequcnce on hand firstly using the DWT (discrete wavclet transform) , and then selects the higher frequency pixel values of an interval to reconstruct the background according to the pixels clustering combing dual-threshold with similar classes merged method, at last verifies background reconstruction accuracy by quoting the evaluation criteria of image matches. Experimental results demonstrate that the proposed method can extract better background to achieve efficient and integrated moving object segmentation.