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Various researchers discuss that in order to denoise the video sequences, spatio-temporal filtering is required which identifies noise and preserves the edges. In the first stage, the video sequences are analyzed for the removal of redundant frames. This is done by using the video fragmentation process in the MATLAB toolbox. In the next stage, color smoothing is applied to the target frames for processing the flat regions and identifying all the noisy pixels. In the final stage, an improvised multiresolution wavelet transform based anisotropic diffusion filtering is applied which enhances the denoising process in horizontal, vertical, and diagonal sub bands of the video frame signal. The proposed technique can remove the speckle noise and estimate the motion by preserving the minute details of the processed video frames.<\/jats:p>","DOI":"10.4018\/ijmdem.2020010101","type":"journal-article","created":{"date-parts":[[2020,1,17]],"date-time":"2020-01-17T19:02:54Z","timestamp":1579287774000},"page":"1-14","source":"Crossref","is-referenced-by-count":2,"title":["Multiresolution Wavelet Transform Based Anisotropic Diffusion for Removing Speckle Noise in a Real-Time Vision-Based Database"],"prefix":"10.4018","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3577-9811","authenticated-orcid":true,"given":"Rohini","family":"Mahajan","sequence":"first","affiliation":[{"name":"Central University of Jammu, India"}]},{"given":"Devanand","family":"Padha","sequence":"additional","affiliation":[{"name":"Central University of Jammu, India"}]}],"member":"2432","reference":[{"key":"IJMDEM.2020010101-0","doi-asserted-by":"publisher","DOI":"10.1504\/IJIEI.2016.080514"},{"key":"IJMDEM.2020010101-1"},{"key":"IJMDEM.2020010101-2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2016.04.018"},{"key":"IJMDEM.2020010101-3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5539960"},{"key":"IJMDEM.2020010101-4","doi-asserted-by":"publisher","DOI":"10.5121\/sipij.2015.6206"},{"issue":"01","key":"IJMDEM.2020010101-5","first-page":"36","article-title":"Object Detection and tracking in Video Sequences. 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